This project begins from the simple premise that the task of
endogenizing the NK search landscape can be done by representing the
search environment as a binary bipartite network of M
actors affiliating with N components. This bipartite
network can be then be analyzed according to the Stochastic
Actor-Oriented Model (SAOM) (Snijders,
1996).
Thus, the Stochastic Actor-Oriented MNK model, abbrivated
SaoMNK, is designed for running strategic search
simulation, testing, and experimentation by leveraging the
RSiena package, an R implementation of
Simulation Investigation for Empirical Network Analysis (SIENA).
This tutorial offers a basic introduction to SaoMNK.
############### Load R6 Class DEPENDENCIES ############################
## Biparite Environment Search Simulation Class
SaomNkRSienaBiEnv <- source(file.path(dir_r, 'SAOM_NK_R6_model.R'))$value
# ## RSiena search Class
# SaomNkRSienaBiEnv_search_rsiena <- source(file.path(dir_proj, 'SAOM_NK_R6_search_rsiena_model.R'))$value
## default settings: Users do not change; TODO: implment within restricted class attributes
DV_NAME <- 'self$bipartite_rsienaDV'
#
steps_per_actor <- 50
#
environ_params <- list(
M = 12, ## Actors
N = 12, ## Components
BI_PROB = 1, ## Environmental Density (DGP hyperparameter)
component_matrix_start = 'rand', ##**TODO** Implement: 'rand','modular','semi-modular',...
rand_seed = 1234,
plot_init = F,
name = '_test_tutorial_nb_'
)
#
env1 <- SaomNkRSienaBiEnv$new(environ_params)
##
## TEST FROM CALLED CLASS INIT *BEFORE* BASE INIT
##
## CALLED _BASE_ INIT
##
## TEST FROM CALLED CLASS INIT *AFTER* BASE INIT
print(c(env1$M, env1$N))
## [1] 12 12
library(Matrix) # For block diagonal matrices
#
create_block_diag <- function(N, B) {
# Determine the approximate block size
block_sizes <- rep(N %/% B, B) # Equal-sized blocks
block_sizes[1:(N %% B)] <- if (N %% B == 0) {
block_sizes[1:(N %% B)] # Adjust for remainder
} else {
block_sizes[1:(N %% B)] + 1
}
# Create individual binary blocks
blocks <- lapply(block_sizes, function(s) matrix(1, nrow = s, ncol = s))
# Combine blocks into a block diagonal matrix
block_diag_matrix <- as.matrix(bdiag(blocks)) # Convert sparse to standard matrix
# Ensure exact NxN dimensions
block_diag_matrix <- block_diag_matrix[1:N, 1:N] # Trim to N x N
# return
return(block_diag_matrix)
}
# Example usage:
N <- 6 # Number of rows/columns
B <- 2 # Number of blocks
block_matrix <- create_block_diag(8, 2)
# Print the matrix
print(block_matrix)
## [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8]
## [1,] 1 1 1 1 0 0 0 0
## [2,] 1 1 1 1 0 0 0 0
## [3,] 1 1 1 1 0 0 0 0
## [4,] 1 1 1 1 0 0 0 0
## [5,] 0 0 0 0 1 1 1 1
## [6,] 0 0 0 0 1 1 1 1
## [7,] 0 0 0 0 1 1 1 1
## [8,] 0 0 0 0 1 1 1 1
SAOM Objective Function serves as the stochastic actor’s utility function for strategic search.
#
strategies <- list(
egoX = c(-1, 0, 1),
inPopX = c( 1, 0, -1)
)
## 2.b. Component Payoffs vector
set.seed(12345)
component_payoffs <- runif(environ_params$N, min = 0, max = 1)
## 2. Strategies sets the objective function as a linear combination of network stats across DVs
#
actor_strats_list <- lapply(strategies, function(strat) rep(strat, environ_params$M/length(strat)) )
component_int_mat <- create_block_diag(environ_params$N, round(environ_params$N/3))
# dyad_cov_XWX <- ( outer(component_payoffs, component_payoffs, '*') *
# create_block_diag(environ_params$N, round(environ_params$N/3))
# )
dyad_cov_X <- matrix(runif(n = environ_params$N*environ_params$M, min = -.5, max= 1), nrow=environ_params$M)
# dyad_cov_X <- matrix(runif(environ_params$N*environ_params$M) - runif(environ_params$N*environ_params$M),
# nrow=environ_params$M)
# dyad_cov_XWX_X <- t( dyad_cov_XWX %*% t(dyad_cov_X) )
#
structure_model <- list(
dv_bipartite = list(
name = 'self$bipartite_rsienaDV',
effects = list( ##**STRUCTURAL EFFECTS -- dyadic/network endogeneity sources**
list(effect='density', parameter= 0, dv_name=DV_NAME, fix=T ), ##interaction1 = NULL
list(effect='inPop', parameter= 0, dv_name=DV_NAME, fix=T ), #interaction1 = NUL
list(effect='outAct', parameter= 0, dv_name=DV_NAME, fix=T )
),
## COVARIATE EFFECTS
coCovars = list(
##** COMPONENTS : MONADIC CONSTANT COVARIATE EFFECTS **##
# list(effect='altX', parameter= 0, dv_name=DV_NAME, fix=T,
# interaction1='self$component_1_coCovar', x = component_payoffs
# ),
# list(effect='outActX', parameter= 0, dv_name=DV_NAME, fix=T,
# interaction1='self$component_1_coCovar', x = component_payoffs
# ),
##** STRATEGIES : MONADIC CONSTANT COVARIATE EFFECTS **##
list(effect='egoX', parameter= 0, dv_name=DV_NAME, fix=T,
interaction1='self$strat_1_coCovar', x = actor_strats_list[[1]]
), #interaction1 = NULL
list(effect='inPopX', parameter= 0, dv_name=DV_NAME, fix=T,
interaction1='self$strat_2_coCovar', x = actor_strats_list[[2]]
) ,
list(effect='totInDist2', parameter= 0, dv_name=DV_NAME, fix=T,
interaction1='self$strat_3_coCovar', x = (actor_strats_list[[1]] - actor_strats_list[[2]] )
)
),
##**MONADIC TIME-VARYING COVARIATE EFFECTS -- DYNAMIC STRATEGY PROGRAMS**
varCovars = list(),
##**DYADIC CONSTANT COVARIATE EFFECTS -- EXOGENOUS INTERACTION MATRIX**
coDyadCovars = list(
list(effect='XWX', parameter= .1, dv_name=DV_NAME, fix=T, nodeSet=c('COMPONENTS','COMPONENTS'),##if M=N, must provide nodeSet
interaction1='self$component_1_coDyadCovar',
x = component_int_mat ## component-[actor]-component dyads
) ,
list(effect='X', parameter= 0, dv_name=DV_NAME, fix=T, nodeSet=c('ACTORS','COMPONENTS'), ##if M=N, must provide nodeSet
interaction1='self$component_2_coDyadCovar',
x = dyad_cov_X ## deltas = changes of payoff contributions from each actor-component
)
),
##**DYADIC TIME-VARYING COVARIATE EFFECTS -- DYNAMIC INTERACTION MATRIX**
varDyadCovars = list(),
interactions = list(
list(effect='egoX|XWX', parameter= 0, dv_name=DV_NAME, fix=T,
interaction1='self$strat_1_coCovar',
interaction2='self$component_1_coDyadCovar'
),
list(effect='inPopX|X', parameter= 0, dv_name=DV_NAME, fix=T,
interaction1='self$strat_2_coCovar',
interaction2='self$component_2_coDyadCovar'
),
list(effect='totInDist2|X', parameter= 0, dv_name=DV_NAME, fix=T,
interaction1='self$strat_3_coCovar',
interaction2='self$component_2_coDyadCovar'
)
)
)
)
env1$preview_effects(structure_model, filter=FALSE)
## Effects documentation written to file C:/Users/sdr8y/OneDrive - University of Missouri/Research/Search_networks/SaoMNK/R/_rsiena_effects_doc_.html .
# ## Uncomment for HTML output with filterable data table
# env1$preview_effects(structure_model, filter=TRUE)
## TODO: PICK UP WITH coDydCovar Interation Matrix
## Run Rsiena search using variable parameters in theta_matrix
env1$search_rsiena(
structure_model,
iterations = env1$M * steps_per_actor,
digits = 4,
run_seed = 12345
)
##
##
## self$rsiena_data :
##
## Dependent variables: self$bipartite_rsienaDV
## Number of observations: 2
##
## Nodesets ACTORS COMPONENTS
## Number of nodes 12 12
##
## Dependent variable self$bipartite_rsienaDV
## Type bipartite
## Observations 2
## First nodeset ACTORS
## Second nodeset COMPONENTS
## Densities 1 1
##
## Constant covariates: self$strat_1_coCovar, self$strat_2_coCovar, self$strat_3_coCovar
## Constant dyadic covariates: self$component_1_coDyadCovar, self$component_2_coDyadCovar
##
## structural effects i=1, j=1
## $effect
## [1] "density"
##
## $parameter
## [1] 0
##
## $dv_name
## [1] "self$bipartite_rsienaDV"
##
## $fix
## [1] TRUE
##
## effectName include fix test initialValue parm
## 1 outdegree (density) TRUE TRUE FALSE 1.60944 0
## effectName include fix test initialValue parm
## 1 outdegree (density) TRUE TRUE FALSE 0 0
##
## structural effects i=1, j=2
## $effect
## [1] "inPop"
##
## $parameter
## [1] 0
##
## $dv_name
## [1] "self$bipartite_rsienaDV"
##
## $fix
## [1] TRUE
##
## effectName include fix test initialValue parm
## 1 indegree - popularity TRUE TRUE FALSE 0 0
## effectName include fix test initialValue parm
## 1 indegree - popularity TRUE TRUE FALSE 0 0
##
## structural effects i=1, j=3
## $effect
## [1] "outAct"
##
## $parameter
## [1] 0
##
## $dv_name
## [1] "self$bipartite_rsienaDV"
##
## $fix
## [1] TRUE
##
## effectName include fix test initialValue parm
## 1 outdegree - activity TRUE TRUE FALSE 0 0
## effectName include fix test initialValue parm
## 1 outdegree - activity TRUE TRUE FALSE 0 0
##
## coCovars i=1, j=1
## $effect
## [1] "egoX"
##
## $parameter
## [1] 0
##
## $dv_name
## [1] "self$bipartite_rsienaDV"
##
## $fix
## [1] TRUE
##
## $interaction1
## [1] "self$strat_1_coCovar"
##
## $x
## [1] -1 0 1 -1 0 1 -1 0 1 -1 0 1
##
## effectName include fix test initialValue parm
## 1 self$strat_1_coCovar ego TRUE TRUE FALSE 0 0
## effectName include fix test initialValue parm
## 1 self$strat_1_coCovar ego TRUE TRUE FALSE 0 0
##
## coCovars i=1, j=2
## $effect
## [1] "inPopX"
##
## $parameter
## [1] 0
##
## $dv_name
## [1] "self$bipartite_rsienaDV"
##
## $fix
## [1] TRUE
##
## $interaction1
## [1] "self$strat_2_coCovar"
##
## $x
## [1] 1 0 -1 1 0 -1 1 0 -1 1 0 -1
##
## effectName include fix test initialValue
## 1 ind. pop.^(1/#) weighted self$strat_2_coCovar TRUE TRUE FALSE 0
## parm
## 1 1
## effectName include fix test initialValue
## 1 ind. pop.^(1/#) weighted self$strat_2_coCovar TRUE TRUE FALSE 0
## parm
## 1 0
##
## coCovars i=1, j=3
## $effect
## [1] "totInDist2"
##
## $parameter
## [1] 0
##
## $dv_name
## [1] "self$bipartite_rsienaDV"
##
## $fix
## [1] TRUE
##
## $interaction1
## [1] "self$strat_3_coCovar"
##
## $x
## [1] -2 0 2 -2 0 2 -2 0 2 -2 0 2
##
## effectName include fix test initialValue parm
## 1 self$strat_3_coCovar tot in-alter dist 2 TRUE TRUE FALSE 0 0
## effectName include fix test initialValue parm
## 1 self$strat_3_coCovar tot in-alter dist 2 TRUE TRUE FALSE 0 0
##
## coDyadCovars i=1, j=1
## $effect
## [1] "XWX"
##
## $parameter
## [1] 0.1
##
## $dv_name
## [1] "self$bipartite_rsienaDV"
##
## $fix
## [1] TRUE
##
## $nodeSet
## [1] "COMPONENTS" "COMPONENTS"
##
## $interaction1
## [1] "self$component_1_coDyadCovar"
##
## $x
## [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12]
## [1,] 1 1 1 0 0 0 0 0 0 0 0 0
## [2,] 1 1 1 0 0 0 0 0 0 0 0 0
## [3,] 1 1 1 0 0 0 0 0 0 0 0 0
## [4,] 0 0 0 1 1 1 0 0 0 0 0 0
## [5,] 0 0 0 1 1 1 0 0 0 0 0 0
## [6,] 0 0 0 1 1 1 0 0 0 0 0 0
## [7,] 0 0 0 0 0 0 1 1 1 0 0 0
## [8,] 0 0 0 0 0 0 1 1 1 0 0 0
## [9,] 0 0 0 0 0 0 1 1 1 0 0 0
## [10,] 0 0 0 0 0 0 0 0 0 1 1 1
## [11,] 0 0 0 0 0 0 0 0 0 1 1 1
## [12,] 0 0 0 0 0 0 0 0 0 1 1 1
##
## effectName include fix test initialValue
## 1 XW=>X closure of self$component_1_coDyadCovar TRUE TRUE FALSE 0
## parm
## 1 0
## effectName include fix test initialValue
## 1 XW=>X closure of self$component_1_coDyadCovar TRUE TRUE FALSE 0
## parm
## 1 0.1
##
## coDyadCovars i=1, j=2
## $effect
## [1] "X"
##
## $parameter
## [1] 0
##
## $dv_name
## [1] "self$bipartite_rsienaDV"
##
## $fix
## [1] TRUE
##
## $nodeSet
## [1] "ACTORS" "COMPONENTS"
##
## $interaction1
## [1] "self$component_2_coDyadCovar"
##
## $x
## [,1] [,2] [,3] [,4] [,5] [,6]
## [1,] 0.603527429 0.46681395 0.80319235 -0.41741927 0.6873517 0.059404367
## [2,] -0.498295120 0.08474273 0.85623200 0.43831420 -0.1119735 0.003707558
## [3,] 0.086805003 0.54781546 0.42613685 0.94670543 0.9789757 -0.427622971
## [4,] 0.193741981 0.31608680 -0.29895255 0.74095430 0.6353106 0.428421309
## [5,] 0.082215972 -0.16029923 0.67328992 -0.02745765 0.9696674 0.942170938
## [6,] 0.103727713 0.22683663 0.14379823 -0.18046182 -0.1715782 0.482440764
## [7,] -0.231554623 0.68951075 0.89091096 0.59874418 0.9230608 0.265437987
## [8,] 0.927488131 -0.49101856 0.65986484 0.24886153 -0.2758131 -0.274852684
## [9,] 0.180592110 -0.21843133 -0.11047813 0.59465796 0.4005355 0.805671821
## [10,] -0.009871387 0.52275043 -0.01816299 -0.37949593 0.9196461 0.271662517
## [11,] 0.948122985 0.05515619 -0.40970726 0.15329573 0.5325300 -0.487028130
## [12,] 0.561222816 0.04243836 -0.43481532 -0.14512932 0.2583006 -0.471207852
## [,7] [,8] [,9] [,10] [,11] [,12]
## [1,] -0.28323215 0.5801748 -0.12332339 0.33918510 0.7191507 -0.27948818
## [2,] -0.04245237 0.6249194 -0.17739638 0.27237634 0.4947419 0.93860569
## [3,] 0.73848529 -0.3565392 0.41421407 -0.36543221 0.9167120 0.98516567
## [4,] 0.25351696 0.0967388 0.07516695 0.52487586 0.8122661 0.24465896
## [5,] 0.70535894 -0.0583019 0.63290657 0.56495807 0.5460568 0.87947147
## [6,] -0.40904003 0.4258805 0.06960436 0.70034733 -0.2224387 0.05819521
## [7,] 0.89193270 0.9614112 0.69245810 0.91611762 -0.3536835 0.74058617
## [8,] 0.71226783 0.4273181 0.85853670 -0.22003079 0.7116400 0.33856442
## [9,] -0.38177999 0.2820538 0.97603926 -0.08203658 0.2826665 0.69350681
## [10,] 0.40139242 0.8537557 0.38192196 0.66139493 0.5403110 0.02803262
## [11,] 0.57216982 0.4561816 -0.48580392 -0.44982858 -0.1755056 -0.18720849
## [12,] 0.27076848 0.7964517 -0.01881190 0.50787721 0.4449143 0.67717094
##
## There is no effect with short name X,
## and with interaction1 = <>, interaction2 = <>, and type = <eval>,
## for dependent variable self$bipartite_rsienaDV .
## See effectsDocumentation() for this effects object.
## effectName include fix test initialValue parm
## 1 self$component_2_coDyadCovar TRUE TRUE FALSE 0 0
##
## interactions i=1, j=1
## $effect
## [1] "egoX|XWX"
##
## $parameter
## [1] 0
##
## $dv_name
## [1] "self$bipartite_rsienaDV"
##
## $fix
## [1] TRUE
##
## $interaction1
## [1] "self$strat_1_coCovar"
##
## $interaction2
## [1] "self$component_1_coDyadCovar"
##
## $effects
## [1] "egoX" "XWX"
##
## effectName
## 1 self$strat_1_coCovar ego x XW=>X closure of self$component_1_coDyadCovar
## include fix test initialValue parm effect1 effect2
## 1 TRUE TRUE FALSE 0 0 89 81
##
## interactions i=1, j=2
## $effect
## [1] "inPopX|X"
##
## $parameter
## [1] 0
##
## $dv_name
## [1] "self$bipartite_rsienaDV"
##
## $fix
## [1] TRUE
##
## $interaction1
## [1] "self$strat_2_coCovar"
##
## $interaction2
## [1] "self$component_2_coDyadCovar"
##
## $effects
## [1] "inPopX" "X"
##
## effectName
## 1 ind. pop.^(1/0) weighted self$strat_2_coCovar x self$component_2_coDyadCovar
## include fix test initialValue parm effect1 effect2
## 1 TRUE TRUE FALSE 0 0 170 86
##
## interactions i=1, j=3
## $effect
## [1] "totInDist2|X"
##
## $parameter
## [1] 0
##
## $dv_name
## [1] "self$bipartite_rsienaDV"
##
## $fix
## [1] TRUE
##
## $interaction1
## [1] "self$strat_3_coCovar"
##
## $interaction2
## [1] "self$component_2_coDyadCovar"
##
## $effects
## [1] "totInDist2" "X"
##
## effectName
## 1 self$strat_3_coCovar tot in-alter dist 2 x self$component_2_coDyadCovar
## include fix test initialValue parm effect1 effect2
## 1 TRUE TRUE FALSE 0 0 209 86
## [1] "density"
## [1] "inPop"
## [1] "outAct"
## [1] "XWX"
## [1] "X"
## [1] "egoX"
## [1] "inPopX"
## [1] "totInDist2"
## [1] "egoX|XWX"
## [1] "inPopX|X"
## [1] "totInDist2|X"
##
##
## theta_matrix :
##
## density inPop outAct XWX X egoX inPopX totInDist2 egoX|XWX inPopX|X
## [1,] 0 0 0 0.1 0 0 0 0 0 0
## [2,] 0 0 0 0.1 0 0 0 0 0 0
## [3,] 0 0 0 0.1 0 0 0 0 0 0
## [4,] 0 0 0 0.1 0 0 0 0 0 0
## [5,] 0 0 0 0.1 0 0 0 0 0 0
## [6,] 0 0 0 0.1 0 0 0 0 0 0
## [7,] 0 0 0 0.1 0 0 0 0 0 0
## [8,] 0 0 0 0.1 0 0 0 0 0 0
## [9,] 0 0 0 0.1 0 0 0 0 0 0
## [10,] 0 0 0 0.1 0 0 0 0 0 0
## [11,] 0 0 0 0.1 0 0 0 0 0 0
## [12,] 0 0 0 0.1 0 0 0 0 0 0
## [13,] 0 0 0 0.1 0 0 0 0 0 0
## [14,] 0 0 0 0.1 0 0 0 0 0 0
## [15,] 0 0 0 0.1 0 0 0 0 0 0
## [16,] 0 0 0 0.1 0 0 0 0 0 0
## [17,] 0 0 0 0.1 0 0 0 0 0 0
## [18,] 0 0 0 0.1 0 0 0 0 0 0
## [19,] 0 0 0 0.1 0 0 0 0 0 0
## [20,] 0 0 0 0.1 0 0 0 0 0 0
## [21,] 0 0 0 0.1 0 0 0 0 0 0
## [22,] 0 0 0 0.1 0 0 0 0 0 0
## [23,] 0 0 0 0.1 0 0 0 0 0 0
## [24,] 0 0 0 0.1 0 0 0 0 0 0
## [25,] 0 0 0 0.1 0 0 0 0 0 0
## [26,] 0 0 0 0.1 0 0 0 0 0 0
## [27,] 0 0 0 0.1 0 0 0 0 0 0
## [28,] 0 0 0 0.1 0 0 0 0 0 0
## [29,] 0 0 0 0.1 0 0 0 0 0 0
## [30,] 0 0 0 0.1 0 0 0 0 0 0
## [31,] 0 0 0 0.1 0 0 0 0 0 0
## [32,] 0 0 0 0.1 0 0 0 0 0 0
## [33,] 0 0 0 0.1 0 0 0 0 0 0
## [34,] 0 0 0 0.1 0 0 0 0 0 0
## [35,] 0 0 0 0.1 0 0 0 0 0 0
## [36,] 0 0 0 0.1 0 0 0 0 0 0
## [37,] 0 0 0 0.1 0 0 0 0 0 0
## [38,] 0 0 0 0.1 0 0 0 0 0 0
## [39,] 0 0 0 0.1 0 0 0 0 0 0
## [40,] 0 0 0 0.1 0 0 0 0 0 0
## [41,] 0 0 0 0.1 0 0 0 0 0 0
## [42,] 0 0 0 0.1 0 0 0 0 0 0
## [43,] 0 0 0 0.1 0 0 0 0 0 0
## [44,] 0 0 0 0.1 0 0 0 0 0 0
## [45,] 0 0 0 0.1 0 0 0 0 0 0
## [46,] 0 0 0 0.1 0 0 0 0 0 0
## [47,] 0 0 0 0.1 0 0 0 0 0 0
## [48,] 0 0 0 0.1 0 0 0 0 0 0
## [49,] 0 0 0 0.1 0 0 0 0 0 0
## [50,] 0 0 0 0.1 0 0 0 0 0 0
## [51,] 0 0 0 0.1 0 0 0 0 0 0
## [52,] 0 0 0 0.1 0 0 0 0 0 0
## [53,] 0 0 0 0.1 0 0 0 0 0 0
## [54,] 0 0 0 0.1 0 0 0 0 0 0
## [55,] 0 0 0 0.1 0 0 0 0 0 0
## [56,] 0 0 0 0.1 0 0 0 0 0 0
## [57,] 0 0 0 0.1 0 0 0 0 0 0
## [58,] 0 0 0 0.1 0 0 0 0 0 0
## [59,] 0 0 0 0.1 0 0 0 0 0 0
## [60,] 0 0 0 0.1 0 0 0 0 0 0
## [61,] 0 0 0 0.1 0 0 0 0 0 0
## [62,] 0 0 0 0.1 0 0 0 0 0 0
## [63,] 0 0 0 0.1 0 0 0 0 0 0
## [64,] 0 0 0 0.1 0 0 0 0 0 0
## [65,] 0 0 0 0.1 0 0 0 0 0 0
## [66,] 0 0 0 0.1 0 0 0 0 0 0
## [67,] 0 0 0 0.1 0 0 0 0 0 0
## [68,] 0 0 0 0.1 0 0 0 0 0 0
## [69,] 0 0 0 0.1 0 0 0 0 0 0
## [70,] 0 0 0 0.1 0 0 0 0 0 0
## [71,] 0 0 0 0.1 0 0 0 0 0 0
## [72,] 0 0 0 0.1 0 0 0 0 0 0
## [73,] 0 0 0 0.1 0 0 0 0 0 0
## [74,] 0 0 0 0.1 0 0 0 0 0 0
## [75,] 0 0 0 0.1 0 0 0 0 0 0
## [76,] 0 0 0 0.1 0 0 0 0 0 0
## [77,] 0 0 0 0.1 0 0 0 0 0 0
## [78,] 0 0 0 0.1 0 0 0 0 0 0
## [79,] 0 0 0 0.1 0 0 0 0 0 0
## [80,] 0 0 0 0.1 0 0 0 0 0 0
## [81,] 0 0 0 0.1 0 0 0 0 0 0
## [82,] 0 0 0 0.1 0 0 0 0 0 0
## [83,] 0 0 0 0.1 0 0 0 0 0 0
## [84,] 0 0 0 0.1 0 0 0 0 0 0
## [85,] 0 0 0 0.1 0 0 0 0 0 0
## [86,] 0 0 0 0.1 0 0 0 0 0 0
## [87,] 0 0 0 0.1 0 0 0 0 0 0
## [88,] 0 0 0 0.1 0 0 0 0 0 0
## [89,] 0 0 0 0.1 0 0 0 0 0 0
## [90,] 0 0 0 0.1 0 0 0 0 0 0
## [91,] 0 0 0 0.1 0 0 0 0 0 0
## [92,] 0 0 0 0.1 0 0 0 0 0 0
## [93,] 0 0 0 0.1 0 0 0 0 0 0
## [94,] 0 0 0 0.1 0 0 0 0 0 0
## [95,] 0 0 0 0.1 0 0 0 0 0 0
## [96,] 0 0 0 0.1 0 0 0 0 0 0
## [97,] 0 0 0 0.1 0 0 0 0 0 0
## [98,] 0 0 0 0.1 0 0 0 0 0 0
## [99,] 0 0 0 0.1 0 0 0 0 0 0
## [100,] 0 0 0 0.1 0 0 0 0 0 0
## [101,] 0 0 0 0.1 0 0 0 0 0 0
## [102,] 0 0 0 0.1 0 0 0 0 0 0
## [103,] 0 0 0 0.1 0 0 0 0 0 0
## [104,] 0 0 0 0.1 0 0 0 0 0 0
## [105,] 0 0 0 0.1 0 0 0 0 0 0
## [106,] 0 0 0 0.1 0 0 0 0 0 0
## [107,] 0 0 0 0.1 0 0 0 0 0 0
## [108,] 0 0 0 0.1 0 0 0 0 0 0
## [109,] 0 0 0 0.1 0 0 0 0 0 0
## [110,] 0 0 0 0.1 0 0 0 0 0 0
## [111,] 0 0 0 0.1 0 0 0 0 0 0
## [112,] 0 0 0 0.1 0 0 0 0 0 0
## [113,] 0 0 0 0.1 0 0 0 0 0 0
## [114,] 0 0 0 0.1 0 0 0 0 0 0
## [115,] 0 0 0 0.1 0 0 0 0 0 0
## [116,] 0 0 0 0.1 0 0 0 0 0 0
## [117,] 0 0 0 0.1 0 0 0 0 0 0
## [118,] 0 0 0 0.1 0 0 0 0 0 0
## [119,] 0 0 0 0.1 0 0 0 0 0 0
## [120,] 0 0 0 0.1 0 0 0 0 0 0
## [121,] 0 0 0 0.1 0 0 0 0 0 0
## [122,] 0 0 0 0.1 0 0 0 0 0 0
## [123,] 0 0 0 0.1 0 0 0 0 0 0
## [124,] 0 0 0 0.1 0 0 0 0 0 0
## [125,] 0 0 0 0.1 0 0 0 0 0 0
## [126,] 0 0 0 0.1 0 0 0 0 0 0
## [127,] 0 0 0 0.1 0 0 0 0 0 0
## [128,] 0 0 0 0.1 0 0 0 0 0 0
## [129,] 0 0 0 0.1 0 0 0 0 0 0
## [130,] 0 0 0 0.1 0 0 0 0 0 0
## [131,] 0 0 0 0.1 0 0 0 0 0 0
## [132,] 0 0 0 0.1 0 0 0 0 0 0
## [133,] 0 0 0 0.1 0 0 0 0 0 0
## [134,] 0 0 0 0.1 0 0 0 0 0 0
## [135,] 0 0 0 0.1 0 0 0 0 0 0
## [136,] 0 0 0 0.1 0 0 0 0 0 0
## [137,] 0 0 0 0.1 0 0 0 0 0 0
## [138,] 0 0 0 0.1 0 0 0 0 0 0
## [139,] 0 0 0 0.1 0 0 0 0 0 0
## [140,] 0 0 0 0.1 0 0 0 0 0 0
## [141,] 0 0 0 0.1 0 0 0 0 0 0
## [142,] 0 0 0 0.1 0 0 0 0 0 0
## [143,] 0 0 0 0.1 0 0 0 0 0 0
## [144,] 0 0 0 0.1 0 0 0 0 0 0
## [145,] 0 0 0 0.1 0 0 0 0 0 0
## [146,] 0 0 0 0.1 0 0 0 0 0 0
## [147,] 0 0 0 0.1 0 0 0 0 0 0
## [148,] 0 0 0 0.1 0 0 0 0 0 0
## [149,] 0 0 0 0.1 0 0 0 0 0 0
## [150,] 0 0 0 0.1 0 0 0 0 0 0
## [151,] 0 0 0 0.1 0 0 0 0 0 0
## [152,] 0 0 0 0.1 0 0 0 0 0 0
## [153,] 0 0 0 0.1 0 0 0 0 0 0
## [154,] 0 0 0 0.1 0 0 0 0 0 0
## [155,] 0 0 0 0.1 0 0 0 0 0 0
## [156,] 0 0 0 0.1 0 0 0 0 0 0
## [157,] 0 0 0 0.1 0 0 0 0 0 0
## [158,] 0 0 0 0.1 0 0 0 0 0 0
## [159,] 0 0 0 0.1 0 0 0 0 0 0
## [160,] 0 0 0 0.1 0 0 0 0 0 0
## [161,] 0 0 0 0.1 0 0 0 0 0 0
## [162,] 0 0 0 0.1 0 0 0 0 0 0
## [163,] 0 0 0 0.1 0 0 0 0 0 0
## [164,] 0 0 0 0.1 0 0 0 0 0 0
## [165,] 0 0 0 0.1 0 0 0 0 0 0
## [166,] 0 0 0 0.1 0 0 0 0 0 0
## [167,] 0 0 0 0.1 0 0 0 0 0 0
## [168,] 0 0 0 0.1 0 0 0 0 0 0
## [169,] 0 0 0 0.1 0 0 0 0 0 0
## [170,] 0 0 0 0.1 0 0 0 0 0 0
## [171,] 0 0 0 0.1 0 0 0 0 0 0
## [172,] 0 0 0 0.1 0 0 0 0 0 0
## [173,] 0 0 0 0.1 0 0 0 0 0 0
## [174,] 0 0 0 0.1 0 0 0 0 0 0
## [175,] 0 0 0 0.1 0 0 0 0 0 0
## [176,] 0 0 0 0.1 0 0 0 0 0 0
## [177,] 0 0 0 0.1 0 0 0 0 0 0
## [178,] 0 0 0 0.1 0 0 0 0 0 0
## [179,] 0 0 0 0.1 0 0 0 0 0 0
## [180,] 0 0 0 0.1 0 0 0 0 0 0
## [181,] 0 0 0 0.1 0 0 0 0 0 0
## [182,] 0 0 0 0.1 0 0 0 0 0 0
## [183,] 0 0 0 0.1 0 0 0 0 0 0
## [184,] 0 0 0 0.1 0 0 0 0 0 0
## [185,] 0 0 0 0.1 0 0 0 0 0 0
## [186,] 0 0 0 0.1 0 0 0 0 0 0
## [187,] 0 0 0 0.1 0 0 0 0 0 0
## [188,] 0 0 0 0.1 0 0 0 0 0 0
## [189,] 0 0 0 0.1 0 0 0 0 0 0
## [190,] 0 0 0 0.1 0 0 0 0 0 0
## [191,] 0 0 0 0.1 0 0 0 0 0 0
## [192,] 0 0 0 0.1 0 0 0 0 0 0
## [193,] 0 0 0 0.1 0 0 0 0 0 0
## [194,] 0 0 0 0.1 0 0 0 0 0 0
## [195,] 0 0 0 0.1 0 0 0 0 0 0
## [196,] 0 0 0 0.1 0 0 0 0 0 0
## [197,] 0 0 0 0.1 0 0 0 0 0 0
## [198,] 0 0 0 0.1 0 0 0 0 0 0
## [199,] 0 0 0 0.1 0 0 0 0 0 0
## [200,] 0 0 0 0.1 0 0 0 0 0 0
## [201,] 0 0 0 0.1 0 0 0 0 0 0
## [202,] 0 0 0 0.1 0 0 0 0 0 0
## [203,] 0 0 0 0.1 0 0 0 0 0 0
## [204,] 0 0 0 0.1 0 0 0 0 0 0
## [205,] 0 0 0 0.1 0 0 0 0 0 0
## [206,] 0 0 0 0.1 0 0 0 0 0 0
## [207,] 0 0 0 0.1 0 0 0 0 0 0
## [208,] 0 0 0 0.1 0 0 0 0 0 0
## [209,] 0 0 0 0.1 0 0 0 0 0 0
## [210,] 0 0 0 0.1 0 0 0 0 0 0
## [211,] 0 0 0 0.1 0 0 0 0 0 0
## [212,] 0 0 0 0.1 0 0 0 0 0 0
## [213,] 0 0 0 0.1 0 0 0 0 0 0
## [214,] 0 0 0 0.1 0 0 0 0 0 0
## [215,] 0 0 0 0.1 0 0 0 0 0 0
## [216,] 0 0 0 0.1 0 0 0 0 0 0
## [217,] 0 0 0 0.1 0 0 0 0 0 0
## [218,] 0 0 0 0.1 0 0 0 0 0 0
## [219,] 0 0 0 0.1 0 0 0 0 0 0
## [220,] 0 0 0 0.1 0 0 0 0 0 0
## [221,] 0 0 0 0.1 0 0 0 0 0 0
## [222,] 0 0 0 0.1 0 0 0 0 0 0
## [223,] 0 0 0 0.1 0 0 0 0 0 0
## [224,] 0 0 0 0.1 0 0 0 0 0 0
## [225,] 0 0 0 0.1 0 0 0 0 0 0
## [226,] 0 0 0 0.1 0 0 0 0 0 0
## [227,] 0 0 0 0.1 0 0 0 0 0 0
## [228,] 0 0 0 0.1 0 0 0 0 0 0
## [229,] 0 0 0 0.1 0 0 0 0 0 0
## [230,] 0 0 0 0.1 0 0 0 0 0 0
## [231,] 0 0 0 0.1 0 0 0 0 0 0
## [232,] 0 0 0 0.1 0 0 0 0 0 0
## [233,] 0 0 0 0.1 0 0 0 0 0 0
## [234,] 0 0 0 0.1 0 0 0 0 0 0
## [235,] 0 0 0 0.1 0 0 0 0 0 0
## [236,] 0 0 0 0.1 0 0 0 0 0 0
## [237,] 0 0 0 0.1 0 0 0 0 0 0
## [238,] 0 0 0 0.1 0 0 0 0 0 0
## [239,] 0 0 0 0.1 0 0 0 0 0 0
## [240,] 0 0 0 0.1 0 0 0 0 0 0
## [241,] 0 0 0 0.1 0 0 0 0 0 0
## [242,] 0 0 0 0.1 0 0 0 0 0 0
## [243,] 0 0 0 0.1 0 0 0 0 0 0
## [244,] 0 0 0 0.1 0 0 0 0 0 0
## [245,] 0 0 0 0.1 0 0 0 0 0 0
## [246,] 0 0 0 0.1 0 0 0 0 0 0
## [247,] 0 0 0 0.1 0 0 0 0 0 0
## [248,] 0 0 0 0.1 0 0 0 0 0 0
## [249,] 0 0 0 0.1 0 0 0 0 0 0
## [250,] 0 0 0 0.1 0 0 0 0 0 0
## [251,] 0 0 0 0.1 0 0 0 0 0 0
## [252,] 0 0 0 0.1 0 0 0 0 0 0
## [253,] 0 0 0 0.1 0 0 0 0 0 0
## [254,] 0 0 0 0.1 0 0 0 0 0 0
## [255,] 0 0 0 0.1 0 0 0 0 0 0
## [256,] 0 0 0 0.1 0 0 0 0 0 0
## [257,] 0 0 0 0.1 0 0 0 0 0 0
## [258,] 0 0 0 0.1 0 0 0 0 0 0
## [259,] 0 0 0 0.1 0 0 0 0 0 0
## [260,] 0 0 0 0.1 0 0 0 0 0 0
## [261,] 0 0 0 0.1 0 0 0 0 0 0
## [262,] 0 0 0 0.1 0 0 0 0 0 0
## [263,] 0 0 0 0.1 0 0 0 0 0 0
## [264,] 0 0 0 0.1 0 0 0 0 0 0
## [265,] 0 0 0 0.1 0 0 0 0 0 0
## [266,] 0 0 0 0.1 0 0 0 0 0 0
## [267,] 0 0 0 0.1 0 0 0 0 0 0
## [268,] 0 0 0 0.1 0 0 0 0 0 0
## [269,] 0 0 0 0.1 0 0 0 0 0 0
## [270,] 0 0 0 0.1 0 0 0 0 0 0
## [271,] 0 0 0 0.1 0 0 0 0 0 0
## [272,] 0 0 0 0.1 0 0 0 0 0 0
## [273,] 0 0 0 0.1 0 0 0 0 0 0
## [274,] 0 0 0 0.1 0 0 0 0 0 0
## [275,] 0 0 0 0.1 0 0 0 0 0 0
## [276,] 0 0 0 0.1 0 0 0 0 0 0
## [277,] 0 0 0 0.1 0 0 0 0 0 0
## [278,] 0 0 0 0.1 0 0 0 0 0 0
## [279,] 0 0 0 0.1 0 0 0 0 0 0
## [280,] 0 0 0 0.1 0 0 0 0 0 0
## [281,] 0 0 0 0.1 0 0 0 0 0 0
## [282,] 0 0 0 0.1 0 0 0 0 0 0
## [283,] 0 0 0 0.1 0 0 0 0 0 0
## [284,] 0 0 0 0.1 0 0 0 0 0 0
## [285,] 0 0 0 0.1 0 0 0 0 0 0
## [286,] 0 0 0 0.1 0 0 0 0 0 0
## [287,] 0 0 0 0.1 0 0 0 0 0 0
## [288,] 0 0 0 0.1 0 0 0 0 0 0
## [289,] 0 0 0 0.1 0 0 0 0 0 0
## [290,] 0 0 0 0.1 0 0 0 0 0 0
## [291,] 0 0 0 0.1 0 0 0 0 0 0
## [292,] 0 0 0 0.1 0 0 0 0 0 0
## [293,] 0 0 0 0.1 0 0 0 0 0 0
## [294,] 0 0 0 0.1 0 0 0 0 0 0
## [295,] 0 0 0 0.1 0 0 0 0 0 0
## [296,] 0 0 0 0.1 0 0 0 0 0 0
## [297,] 0 0 0 0.1 0 0 0 0 0 0
## [298,] 0 0 0 0.1 0 0 0 0 0 0
## [299,] 0 0 0 0.1 0 0 0 0 0 0
## [300,] 0 0 0 0.1 0 0 0 0 0 0
## [301,] 0 0 0 0.1 0 0 0 0 0 0
## [302,] 0 0 0 0.1 0 0 0 0 0 0
## [303,] 0 0 0 0.1 0 0 0 0 0 0
## [304,] 0 0 0 0.1 0 0 0 0 0 0
## [305,] 0 0 0 0.1 0 0 0 0 0 0
## [306,] 0 0 0 0.1 0 0 0 0 0 0
## [307,] 0 0 0 0.1 0 0 0 0 0 0
## [308,] 0 0 0 0.1 0 0 0 0 0 0
## [309,] 0 0 0 0.1 0 0 0 0 0 0
## [310,] 0 0 0 0.1 0 0 0 0 0 0
## [311,] 0 0 0 0.1 0 0 0 0 0 0
## [312,] 0 0 0 0.1 0 0 0 0 0 0
## [313,] 0 0 0 0.1 0 0 0 0 0 0
## [314,] 0 0 0 0.1 0 0 0 0 0 0
## [315,] 0 0 0 0.1 0 0 0 0 0 0
## [316,] 0 0 0 0.1 0 0 0 0 0 0
## [317,] 0 0 0 0.1 0 0 0 0 0 0
## [318,] 0 0 0 0.1 0 0 0 0 0 0
## [319,] 0 0 0 0.1 0 0 0 0 0 0
## [320,] 0 0 0 0.1 0 0 0 0 0 0
## [321,] 0 0 0 0.1 0 0 0 0 0 0
## [322,] 0 0 0 0.1 0 0 0 0 0 0
## [323,] 0 0 0 0.1 0 0 0 0 0 0
## [324,] 0 0 0 0.1 0 0 0 0 0 0
## [325,] 0 0 0 0.1 0 0 0 0 0 0
## [326,] 0 0 0 0.1 0 0 0 0 0 0
## [327,] 0 0 0 0.1 0 0 0 0 0 0
## [328,] 0 0 0 0.1 0 0 0 0 0 0
## [329,] 0 0 0 0.1 0 0 0 0 0 0
## [330,] 0 0 0 0.1 0 0 0 0 0 0
## [331,] 0 0 0 0.1 0 0 0 0 0 0
## [332,] 0 0 0 0.1 0 0 0 0 0 0
## [333,] 0 0 0 0.1 0 0 0 0 0 0
## [334,] 0 0 0 0.1 0 0 0 0 0 0
## [335,] 0 0 0 0.1 0 0 0 0 0 0
## [336,] 0 0 0 0.1 0 0 0 0 0 0
## [337,] 0 0 0 0.1 0 0 0 0 0 0
## [338,] 0 0 0 0.1 0 0 0 0 0 0
## [339,] 0 0 0 0.1 0 0 0 0 0 0
## [340,] 0 0 0 0.1 0 0 0 0 0 0
## [341,] 0 0 0 0.1 0 0 0 0 0 0
## [342,] 0 0 0 0.1 0 0 0 0 0 0
## [343,] 0 0 0 0.1 0 0 0 0 0 0
## [344,] 0 0 0 0.1 0 0 0 0 0 0
## [345,] 0 0 0 0.1 0 0 0 0 0 0
## [346,] 0 0 0 0.1 0 0 0 0 0 0
## [347,] 0 0 0 0.1 0 0 0 0 0 0
## [348,] 0 0 0 0.1 0 0 0 0 0 0
## [349,] 0 0 0 0.1 0 0 0 0 0 0
## [350,] 0 0 0 0.1 0 0 0 0 0 0
## [351,] 0 0 0 0.1 0 0 0 0 0 0
## [352,] 0 0 0 0.1 0 0 0 0 0 0
## [353,] 0 0 0 0.1 0 0 0 0 0 0
## [354,] 0 0 0 0.1 0 0 0 0 0 0
## [355,] 0 0 0 0.1 0 0 0 0 0 0
## [356,] 0 0 0 0.1 0 0 0 0 0 0
## [357,] 0 0 0 0.1 0 0 0 0 0 0
## [358,] 0 0 0 0.1 0 0 0 0 0 0
## [359,] 0 0 0 0.1 0 0 0 0 0 0
## [360,] 0 0 0 0.1 0 0 0 0 0 0
## [361,] 0 0 0 0.1 0 0 0 0 0 0
## [362,] 0 0 0 0.1 0 0 0 0 0 0
## [363,] 0 0 0 0.1 0 0 0 0 0 0
## [364,] 0 0 0 0.1 0 0 0 0 0 0
## [365,] 0 0 0 0.1 0 0 0 0 0 0
## [366,] 0 0 0 0.1 0 0 0 0 0 0
## [367,] 0 0 0 0.1 0 0 0 0 0 0
## [368,] 0 0 0 0.1 0 0 0 0 0 0
## [369,] 0 0 0 0.1 0 0 0 0 0 0
## [370,] 0 0 0 0.1 0 0 0 0 0 0
## [371,] 0 0 0 0.1 0 0 0 0 0 0
## [372,] 0 0 0 0.1 0 0 0 0 0 0
## [373,] 0 0 0 0.1 0 0 0 0 0 0
## [374,] 0 0 0 0.1 0 0 0 0 0 0
## [375,] 0 0 0 0.1 0 0 0 0 0 0
## [376,] 0 0 0 0.1 0 0 0 0 0 0
## [377,] 0 0 0 0.1 0 0 0 0 0 0
## [378,] 0 0 0 0.1 0 0 0 0 0 0
## [379,] 0 0 0 0.1 0 0 0 0 0 0
## [380,] 0 0 0 0.1 0 0 0 0 0 0
## [381,] 0 0 0 0.1 0 0 0 0 0 0
## [382,] 0 0 0 0.1 0 0 0 0 0 0
## [383,] 0 0 0 0.1 0 0 0 0 0 0
## [384,] 0 0 0 0.1 0 0 0 0 0 0
## [385,] 0 0 0 0.1 0 0 0 0 0 0
## [386,] 0 0 0 0.1 0 0 0 0 0 0
## [387,] 0 0 0 0.1 0 0 0 0 0 0
## [388,] 0 0 0 0.1 0 0 0 0 0 0
## [389,] 0 0 0 0.1 0 0 0 0 0 0
## [390,] 0 0 0 0.1 0 0 0 0 0 0
## [391,] 0 0 0 0.1 0 0 0 0 0 0
## [392,] 0 0 0 0.1 0 0 0 0 0 0
## [393,] 0 0 0 0.1 0 0 0 0 0 0
## [394,] 0 0 0 0.1 0 0 0 0 0 0
## [395,] 0 0 0 0.1 0 0 0 0 0 0
## [396,] 0 0 0 0.1 0 0 0 0 0 0
## [397,] 0 0 0 0.1 0 0 0 0 0 0
## [398,] 0 0 0 0.1 0 0 0 0 0 0
## [399,] 0 0 0 0.1 0 0 0 0 0 0
## [400,] 0 0 0 0.1 0 0 0 0 0 0
## [401,] 0 0 0 0.1 0 0 0 0 0 0
## [402,] 0 0 0 0.1 0 0 0 0 0 0
## [403,] 0 0 0 0.1 0 0 0 0 0 0
## [404,] 0 0 0 0.1 0 0 0 0 0 0
## [405,] 0 0 0 0.1 0 0 0 0 0 0
## [406,] 0 0 0 0.1 0 0 0 0 0 0
## [407,] 0 0 0 0.1 0 0 0 0 0 0
## [408,] 0 0 0 0.1 0 0 0 0 0 0
## [409,] 0 0 0 0.1 0 0 0 0 0 0
## [410,] 0 0 0 0.1 0 0 0 0 0 0
## [411,] 0 0 0 0.1 0 0 0 0 0 0
## [412,] 0 0 0 0.1 0 0 0 0 0 0
## [413,] 0 0 0 0.1 0 0 0 0 0 0
## [414,] 0 0 0 0.1 0 0 0 0 0 0
## [415,] 0 0 0 0.1 0 0 0 0 0 0
## [416,] 0 0 0 0.1 0 0 0 0 0 0
## [417,] 0 0 0 0.1 0 0 0 0 0 0
## [418,] 0 0 0 0.1 0 0 0 0 0 0
## [419,] 0 0 0 0.1 0 0 0 0 0 0
## [420,] 0 0 0 0.1 0 0 0 0 0 0
## [421,] 0 0 0 0.1 0 0 0 0 0 0
## [422,] 0 0 0 0.1 0 0 0 0 0 0
## [423,] 0 0 0 0.1 0 0 0 0 0 0
## [424,] 0 0 0 0.1 0 0 0 0 0 0
## [425,] 0 0 0 0.1 0 0 0 0 0 0
## [426,] 0 0 0 0.1 0 0 0 0 0 0
## [427,] 0 0 0 0.1 0 0 0 0 0 0
## [428,] 0 0 0 0.1 0 0 0 0 0 0
## [429,] 0 0 0 0.1 0 0 0 0 0 0
## [430,] 0 0 0 0.1 0 0 0 0 0 0
## [431,] 0 0 0 0.1 0 0 0 0 0 0
## [432,] 0 0 0 0.1 0 0 0 0 0 0
## [433,] 0 0 0 0.1 0 0 0 0 0 0
## [434,] 0 0 0 0.1 0 0 0 0 0 0
## [435,] 0 0 0 0.1 0 0 0 0 0 0
## [436,] 0 0 0 0.1 0 0 0 0 0 0
## [437,] 0 0 0 0.1 0 0 0 0 0 0
## [438,] 0 0 0 0.1 0 0 0 0 0 0
## [439,] 0 0 0 0.1 0 0 0 0 0 0
## [440,] 0 0 0 0.1 0 0 0 0 0 0
## [441,] 0 0 0 0.1 0 0 0 0 0 0
## [442,] 0 0 0 0.1 0 0 0 0 0 0
## [443,] 0 0 0 0.1 0 0 0 0 0 0
## [444,] 0 0 0 0.1 0 0 0 0 0 0
## [445,] 0 0 0 0.1 0 0 0 0 0 0
## [446,] 0 0 0 0.1 0 0 0 0 0 0
## [447,] 0 0 0 0.1 0 0 0 0 0 0
## [448,] 0 0 0 0.1 0 0 0 0 0 0
## [449,] 0 0 0 0.1 0 0 0 0 0 0
## [450,] 0 0 0 0.1 0 0 0 0 0 0
## [451,] 0 0 0 0.1 0 0 0 0 0 0
## [452,] 0 0 0 0.1 0 0 0 0 0 0
## [453,] 0 0 0 0.1 0 0 0 0 0 0
## [454,] 0 0 0 0.1 0 0 0 0 0 0
## [455,] 0 0 0 0.1 0 0 0 0 0 0
## [456,] 0 0 0 0.1 0 0 0 0 0 0
## [457,] 0 0 0 0.1 0 0 0 0 0 0
## [458,] 0 0 0 0.1 0 0 0 0 0 0
## [459,] 0 0 0 0.1 0 0 0 0 0 0
## [460,] 0 0 0 0.1 0 0 0 0 0 0
## [461,] 0 0 0 0.1 0 0 0 0 0 0
## [462,] 0 0 0 0.1 0 0 0 0 0 0
## [463,] 0 0 0 0.1 0 0 0 0 0 0
## [464,] 0 0 0 0.1 0 0 0 0 0 0
## [465,] 0 0 0 0.1 0 0 0 0 0 0
## [466,] 0 0 0 0.1 0 0 0 0 0 0
## [467,] 0 0 0 0.1 0 0 0 0 0 0
## [468,] 0 0 0 0.1 0 0 0 0 0 0
## [469,] 0 0 0 0.1 0 0 0 0 0 0
## [470,] 0 0 0 0.1 0 0 0 0 0 0
## [471,] 0 0 0 0.1 0 0 0 0 0 0
## [472,] 0 0 0 0.1 0 0 0 0 0 0
## [473,] 0 0 0 0.1 0 0 0 0 0 0
## [474,] 0 0 0 0.1 0 0 0 0 0 0
## [475,] 0 0 0 0.1 0 0 0 0 0 0
## [476,] 0 0 0 0.1 0 0 0 0 0 0
## [477,] 0 0 0 0.1 0 0 0 0 0 0
## [478,] 0 0 0 0.1 0 0 0 0 0 0
## [479,] 0 0 0 0.1 0 0 0 0 0 0
## [480,] 0 0 0 0.1 0 0 0 0 0 0
## [481,] 0 0 0 0.1 0 0 0 0 0 0
## [482,] 0 0 0 0.1 0 0 0 0 0 0
## [483,] 0 0 0 0.1 0 0 0 0 0 0
## [484,] 0 0 0 0.1 0 0 0 0 0 0
## [485,] 0 0 0 0.1 0 0 0 0 0 0
## [486,] 0 0 0 0.1 0 0 0 0 0 0
## [487,] 0 0 0 0.1 0 0 0 0 0 0
## [488,] 0 0 0 0.1 0 0 0 0 0 0
## [489,] 0 0 0 0.1 0 0 0 0 0 0
## [490,] 0 0 0 0.1 0 0 0 0 0 0
## [491,] 0 0 0 0.1 0 0 0 0 0 0
## [492,] 0 0 0 0.1 0 0 0 0 0 0
## [493,] 0 0 0 0.1 0 0 0 0 0 0
## [494,] 0 0 0 0.1 0 0 0 0 0 0
## [495,] 0 0 0 0.1 0 0 0 0 0 0
## [496,] 0 0 0 0.1 0 0 0 0 0 0
## [497,] 0 0 0 0.1 0 0 0 0 0 0
## [498,] 0 0 0 0.1 0 0 0 0 0 0
## [499,] 0 0 0 0.1 0 0 0 0 0 0
## [500,] 0 0 0 0.1 0 0 0 0 0 0
## [501,] 0 0 0 0.1 0 0 0 0 0 0
## [502,] 0 0 0 0.1 0 0 0 0 0 0
## [503,] 0 0 0 0.1 0 0 0 0 0 0
## [504,] 0 0 0 0.1 0 0 0 0 0 0
## [505,] 0 0 0 0.1 0 0 0 0 0 0
## [506,] 0 0 0 0.1 0 0 0 0 0 0
## [507,] 0 0 0 0.1 0 0 0 0 0 0
## [508,] 0 0 0 0.1 0 0 0 0 0 0
## [509,] 0 0 0 0.1 0 0 0 0 0 0
## [510,] 0 0 0 0.1 0 0 0 0 0 0
## [511,] 0 0 0 0.1 0 0 0 0 0 0
## [512,] 0 0 0 0.1 0 0 0 0 0 0
## [513,] 0 0 0 0.1 0 0 0 0 0 0
## [514,] 0 0 0 0.1 0 0 0 0 0 0
## [515,] 0 0 0 0.1 0 0 0 0 0 0
## [516,] 0 0 0 0.1 0 0 0 0 0 0
## [517,] 0 0 0 0.1 0 0 0 0 0 0
## [518,] 0 0 0 0.1 0 0 0 0 0 0
## [519,] 0 0 0 0.1 0 0 0 0 0 0
## [520,] 0 0 0 0.1 0 0 0 0 0 0
## [521,] 0 0 0 0.1 0 0 0 0 0 0
## [522,] 0 0 0 0.1 0 0 0 0 0 0
## [523,] 0 0 0 0.1 0 0 0 0 0 0
## [524,] 0 0 0 0.1 0 0 0 0 0 0
## [525,] 0 0 0 0.1 0 0 0 0 0 0
## [526,] 0 0 0 0.1 0 0 0 0 0 0
## [527,] 0 0 0 0.1 0 0 0 0 0 0
## [528,] 0 0 0 0.1 0 0 0 0 0 0
## [529,] 0 0 0 0.1 0 0 0 0 0 0
## [530,] 0 0 0 0.1 0 0 0 0 0 0
## [531,] 0 0 0 0.1 0 0 0 0 0 0
## [532,] 0 0 0 0.1 0 0 0 0 0 0
## [533,] 0 0 0 0.1 0 0 0 0 0 0
## [534,] 0 0 0 0.1 0 0 0 0 0 0
## [535,] 0 0 0 0.1 0 0 0 0 0 0
## [536,] 0 0 0 0.1 0 0 0 0 0 0
## [537,] 0 0 0 0.1 0 0 0 0 0 0
## [538,] 0 0 0 0.1 0 0 0 0 0 0
## [539,] 0 0 0 0.1 0 0 0 0 0 0
## [540,] 0 0 0 0.1 0 0 0 0 0 0
## [541,] 0 0 0 0.1 0 0 0 0 0 0
## [542,] 0 0 0 0.1 0 0 0 0 0 0
## [543,] 0 0 0 0.1 0 0 0 0 0 0
## [544,] 0 0 0 0.1 0 0 0 0 0 0
## [545,] 0 0 0 0.1 0 0 0 0 0 0
## [546,] 0 0 0 0.1 0 0 0 0 0 0
## [547,] 0 0 0 0.1 0 0 0 0 0 0
## [548,] 0 0 0 0.1 0 0 0 0 0 0
## [549,] 0 0 0 0.1 0 0 0 0 0 0
## [550,] 0 0 0 0.1 0 0 0 0 0 0
## [551,] 0 0 0 0.1 0 0 0 0 0 0
## [552,] 0 0 0 0.1 0 0 0 0 0 0
## [553,] 0 0 0 0.1 0 0 0 0 0 0
## [554,] 0 0 0 0.1 0 0 0 0 0 0
## [555,] 0 0 0 0.1 0 0 0 0 0 0
## [556,] 0 0 0 0.1 0 0 0 0 0 0
## [557,] 0 0 0 0.1 0 0 0 0 0 0
## [558,] 0 0 0 0.1 0 0 0 0 0 0
## [559,] 0 0 0 0.1 0 0 0 0 0 0
## [560,] 0 0 0 0.1 0 0 0 0 0 0
## [561,] 0 0 0 0.1 0 0 0 0 0 0
## [562,] 0 0 0 0.1 0 0 0 0 0 0
## [563,] 0 0 0 0.1 0 0 0 0 0 0
## [564,] 0 0 0 0.1 0 0 0 0 0 0
## [565,] 0 0 0 0.1 0 0 0 0 0 0
## [566,] 0 0 0 0.1 0 0 0 0 0 0
## [567,] 0 0 0 0.1 0 0 0 0 0 0
## [568,] 0 0 0 0.1 0 0 0 0 0 0
## [569,] 0 0 0 0.1 0 0 0 0 0 0
## [570,] 0 0 0 0.1 0 0 0 0 0 0
## [571,] 0 0 0 0.1 0 0 0 0 0 0
## [572,] 0 0 0 0.1 0 0 0 0 0 0
## [573,] 0 0 0 0.1 0 0 0 0 0 0
## [574,] 0 0 0 0.1 0 0 0 0 0 0
## [575,] 0 0 0 0.1 0 0 0 0 0 0
## [576,] 0 0 0 0.1 0 0 0 0 0 0
## [577,] 0 0 0 0.1 0 0 0 0 0 0
## [578,] 0 0 0 0.1 0 0 0 0 0 0
## [579,] 0 0 0 0.1 0 0 0 0 0 0
## [580,] 0 0 0 0.1 0 0 0 0 0 0
## [581,] 0 0 0 0.1 0 0 0 0 0 0
## [582,] 0 0 0 0.1 0 0 0 0 0 0
## [583,] 0 0 0 0.1 0 0 0 0 0 0
## [584,] 0 0 0 0.1 0 0 0 0 0 0
## [585,] 0 0 0 0.1 0 0 0 0 0 0
## [586,] 0 0 0 0.1 0 0 0 0 0 0
## [587,] 0 0 0 0.1 0 0 0 0 0 0
## [588,] 0 0 0 0.1 0 0 0 0 0 0
## [589,] 0 0 0 0.1 0 0 0 0 0 0
## [590,] 0 0 0 0.1 0 0 0 0 0 0
## [591,] 0 0 0 0.1 0 0 0 0 0 0
## [592,] 0 0 0 0.1 0 0 0 0 0 0
## [593,] 0 0 0 0.1 0 0 0 0 0 0
## [594,] 0 0 0 0.1 0 0 0 0 0 0
## [595,] 0 0 0 0.1 0 0 0 0 0 0
## [596,] 0 0 0 0.1 0 0 0 0 0 0
## [597,] 0 0 0 0.1 0 0 0 0 0 0
## [598,] 0 0 0 0.1 0 0 0 0 0 0
## [599,] 0 0 0 0.1 0 0 0 0 0 0
## [600,] 0 0 0 0.1 0 0 0 0 0 0
## totInDist2|X
## [1,] 0
## [2,] 0
## [3,] 0
## [4,] 0
## [5,] 0
## [6,] 0
## [7,] 0
## [8,] 0
## [9,] 0
## [10,] 0
## [11,] 0
## [12,] 0
## [13,] 0
## [14,] 0
## [15,] 0
## [16,] 0
## [17,] 0
## [18,] 0
## [19,] 0
## [20,] 0
## [21,] 0
## [22,] 0
## [23,] 0
## [24,] 0
## [25,] 0
## [26,] 0
## [27,] 0
## [28,] 0
## [29,] 0
## [30,] 0
## [31,] 0
## [32,] 0
## [33,] 0
## [34,] 0
## [35,] 0
## [36,] 0
## [37,] 0
## [38,] 0
## [39,] 0
## [40,] 0
## [41,] 0
## [42,] 0
## [43,] 0
## [44,] 0
## [45,] 0
## [46,] 0
## [47,] 0
## [48,] 0
## [49,] 0
## [50,] 0
## [51,] 0
## [52,] 0
## [53,] 0
## [54,] 0
## [55,] 0
## [56,] 0
## [57,] 0
## [58,] 0
## [59,] 0
## [60,] 0
## [61,] 0
## [62,] 0
## [63,] 0
## [64,] 0
## [65,] 0
## [66,] 0
## [67,] 0
## [68,] 0
## [69,] 0
## [70,] 0
## [71,] 0
## [72,] 0
## [73,] 0
## [74,] 0
## [75,] 0
## [76,] 0
## [77,] 0
## [78,] 0
## [79,] 0
## [80,] 0
## [81,] 0
## [82,] 0
## [83,] 0
## [84,] 0
## [85,] 0
## [86,] 0
## [87,] 0
## [88,] 0
## [89,] 0
## [90,] 0
## [91,] 0
## [92,] 0
## [93,] 0
## [94,] 0
## [95,] 0
## [96,] 0
## [97,] 0
## [98,] 0
## [99,] 0
## [100,] 0
## [101,] 0
## [102,] 0
## [103,] 0
## [104,] 0
## [105,] 0
## [106,] 0
## [107,] 0
## [108,] 0
## [109,] 0
## [110,] 0
## [111,] 0
## [112,] 0
## [113,] 0
## [114,] 0
## [115,] 0
## [116,] 0
## [117,] 0
## [118,] 0
## [119,] 0
## [120,] 0
## [121,] 0
## [122,] 0
## [123,] 0
## [124,] 0
## [125,] 0
## [126,] 0
## [127,] 0
## [128,] 0
## [129,] 0
## [130,] 0
## [131,] 0
## [132,] 0
## [133,] 0
## [134,] 0
## [135,] 0
## [136,] 0
## [137,] 0
## [138,] 0
## [139,] 0
## [140,] 0
## [141,] 0
## [142,] 0
## [143,] 0
## [144,] 0
## [145,] 0
## [146,] 0
## [147,] 0
## [148,] 0
## [149,] 0
## [150,] 0
## [151,] 0
## [152,] 0
## [153,] 0
## [154,] 0
## [155,] 0
## [156,] 0
## [157,] 0
## [158,] 0
## [159,] 0
## [160,] 0
## [161,] 0
## [162,] 0
## [163,] 0
## [164,] 0
## [165,] 0
## [166,] 0
## [167,] 0
## [168,] 0
## [169,] 0
## [170,] 0
## [171,] 0
## [172,] 0
## [173,] 0
## [174,] 0
## [175,] 0
## [176,] 0
## [177,] 0
## [178,] 0
## [179,] 0
## [180,] 0
## [181,] 0
## [182,] 0
## [183,] 0
## [184,] 0
## [185,] 0
## [186,] 0
## [187,] 0
## [188,] 0
## [189,] 0
## [190,] 0
## [191,] 0
## [192,] 0
## [193,] 0
## [194,] 0
## [195,] 0
## [196,] 0
## [197,] 0
## [198,] 0
## [199,] 0
## [200,] 0
## [201,] 0
## [202,] 0
## [203,] 0
## [204,] 0
## [205,] 0
## [206,] 0
## [207,] 0
## [208,] 0
## [209,] 0
## [210,] 0
## [211,] 0
## [212,] 0
## [213,] 0
## [214,] 0
## [215,] 0
## [216,] 0
## [217,] 0
## [218,] 0
## [219,] 0
## [220,] 0
## [221,] 0
## [222,] 0
## [223,] 0
## [224,] 0
## [225,] 0
## [226,] 0
## [227,] 0
## [228,] 0
## [229,] 0
## [230,] 0
## [231,] 0
## [232,] 0
## [233,] 0
## [234,] 0
## [235,] 0
## [236,] 0
## [237,] 0
## [238,] 0
## [239,] 0
## [240,] 0
## [241,] 0
## [242,] 0
## [243,] 0
## [244,] 0
## [245,] 0
## [246,] 0
## [247,] 0
## [248,] 0
## [249,] 0
## [250,] 0
## [251,] 0
## [252,] 0
## [253,] 0
## [254,] 0
## [255,] 0
## [256,] 0
## [257,] 0
## [258,] 0
## [259,] 0
## [260,] 0
## [261,] 0
## [262,] 0
## [263,] 0
## [264,] 0
## [265,] 0
## [266,] 0
## [267,] 0
## [268,] 0
## [269,] 0
## [270,] 0
## [271,] 0
## [272,] 0
## [273,] 0
## [274,] 0
## [275,] 0
## [276,] 0
## [277,] 0
## [278,] 0
## [279,] 0
## [280,] 0
## [281,] 0
## [282,] 0
## [283,] 0
## [284,] 0
## [285,] 0
## [286,] 0
## [287,] 0
## [288,] 0
## [289,] 0
## [290,] 0
## [291,] 0
## [292,] 0
## [293,] 0
## [294,] 0
## [295,] 0
## [296,] 0
## [297,] 0
## [298,] 0
## [299,] 0
## [300,] 0
## [301,] 0
## [302,] 0
## [303,] 0
## [304,] 0
## [305,] 0
## [306,] 0
## [307,] 0
## [308,] 0
## [309,] 0
## [310,] 0
## [311,] 0
## [312,] 0
## [313,] 0
## [314,] 0
## [315,] 0
## [316,] 0
## [317,] 0
## [318,] 0
## [319,] 0
## [320,] 0
## [321,] 0
## [322,] 0
## [323,] 0
## [324,] 0
## [325,] 0
## [326,] 0
## [327,] 0
## [328,] 0
## [329,] 0
## [330,] 0
## [331,] 0
## [332,] 0
## [333,] 0
## [334,] 0
## [335,] 0
## [336,] 0
## [337,] 0
## [338,] 0
## [339,] 0
## [340,] 0
## [341,] 0
## [342,] 0
## [343,] 0
## [344,] 0
## [345,] 0
## [346,] 0
## [347,] 0
## [348,] 0
## [349,] 0
## [350,] 0
## [351,] 0
## [352,] 0
## [353,] 0
## [354,] 0
## [355,] 0
## [356,] 0
## [357,] 0
## [358,] 0
## [359,] 0
## [360,] 0
## [361,] 0
## [362,] 0
## [363,] 0
## [364,] 0
## [365,] 0
## [366,] 0
## [367,] 0
## [368,] 0
## [369,] 0
## [370,] 0
## [371,] 0
## [372,] 0
## [373,] 0
## [374,] 0
## [375,] 0
## [376,] 0
## [377,] 0
## [378,] 0
## [379,] 0
## [380,] 0
## [381,] 0
## [382,] 0
## [383,] 0
## [384,] 0
## [385,] 0
## [386,] 0
## [387,] 0
## [388,] 0
## [389,] 0
## [390,] 0
## [391,] 0
## [392,] 0
## [393,] 0
## [394,] 0
## [395,] 0
## [396,] 0
## [397,] 0
## [398,] 0
## [399,] 0
## [400,] 0
## [401,] 0
## [402,] 0
## [403,] 0
## [404,] 0
## [405,] 0
## [406,] 0
## [407,] 0
## [408,] 0
## [409,] 0
## [410,] 0
## [411,] 0
## [412,] 0
## [413,] 0
## [414,] 0
## [415,] 0
## [416,] 0
## [417,] 0
## [418,] 0
## [419,] 0
## [420,] 0
## [421,] 0
## [422,] 0
## [423,] 0
## [424,] 0
## [425,] 0
## [426,] 0
## [427,] 0
## [428,] 0
## [429,] 0
## [430,] 0
## [431,] 0
## [432,] 0
## [433,] 0
## [434,] 0
## [435,] 0
## [436,] 0
## [437,] 0
## [438,] 0
## [439,] 0
## [440,] 0
## [441,] 0
## [442,] 0
## [443,] 0
## [444,] 0
## [445,] 0
## [446,] 0
## [447,] 0
## [448,] 0
## [449,] 0
## [450,] 0
## [451,] 0
## [452,] 0
## [453,] 0
## [454,] 0
## [455,] 0
## [456,] 0
## [457,] 0
## [458,] 0
## [459,] 0
## [460,] 0
## [461,] 0
## [462,] 0
## [463,] 0
## [464,] 0
## [465,] 0
## [466,] 0
## [467,] 0
## [468,] 0
## [469,] 0
## [470,] 0
## [471,] 0
## [472,] 0
## [473,] 0
## [474,] 0
## [475,] 0
## [476,] 0
## [477,] 0
## [478,] 0
## [479,] 0
## [480,] 0
## [481,] 0
## [482,] 0
## [483,] 0
## [484,] 0
## [485,] 0
## [486,] 0
## [487,] 0
## [488,] 0
## [489,] 0
## [490,] 0
## [491,] 0
## [492,] 0
## [493,] 0
## [494,] 0
## [495,] 0
## [496,] 0
## [497,] 0
## [498,] 0
## [499,] 0
## [500,] 0
## [501,] 0
## [502,] 0
## [503,] 0
## [504,] 0
## [505,] 0
## [506,] 0
## [507,] 0
## [508,] 0
## [509,] 0
## [510,] 0
## [511,] 0
## [512,] 0
## [513,] 0
## [514,] 0
## [515,] 0
## [516,] 0
## [517,] 0
## [518,] 0
## [519,] 0
## [520,] 0
## [521,] 0
## [522,] 0
## [523,] 0
## [524,] 0
## [525,] 0
## [526,] 0
## [527,] 0
## [528,] 0
## [529,] 0
## [530,] 0
## [531,] 0
## [532,] 0
## [533,] 0
## [534,] 0
## [535,] 0
## [536,] 0
## [537,] 0
## [538,] 0
## [539,] 0
## [540,] 0
## [541,] 0
## [542,] 0
## [543,] 0
## [544,] 0
## [545,] 0
## [546,] 0
## [547,] 0
## [548,] 0
## [549,] 0
## [550,] 0
## [551,] 0
## [552,] 0
## [553,] 0
## [554,] 0
## [555,] 0
## [556,] 0
## [557,] 0
## [558,] 0
## [559,] 0
## [560,] 0
## [561,] 0
## [562,] 0
## [563,] 0
## [564,] 0
## [565,] 0
## [566,] 0
## [567,] 0
## [568,] 0
## [569,] 0
## [570,] 0
## [571,] 0
## [572,] 0
## [573,] 0
## [574,] 0
## [575,] 0
## [576,] 0
## [577,] 0
## [578,] 0
## [579,] 0
## [580,] 0
## [581,] 0
## [582,] 0
## [583,] 0
## [584,] 0
## [585,] 0
## [586,] 0
## [587,] 0
## [588,] 0
## [589,] 0
## [590,] 0
## [591,] 0
## [592,] 0
## [593,] 0
## [594,] 0
## [595,] 0
## [596,] 0
## [597,] 0
## [598,] 0
## [599,] 0
## [600,] 0
## If you use this algorithm object, siena07 will create/use an output file C:/Users/sdr8y/OneDrive - University of Missouri/Research/Search_networks/SaoMNK/R/_test_tutorial_nb__173939300521.txt .
##
## Start phase 0
## theta: 0 0 0 0 0 0 0 0 0 0 0
##
## Start phase 3
## Phase 3 Iteration 100 Progress 17%
## Phase 3 Iteration 200 Progress 33%
## Phase 3 Iteration 300 Progress 50%
## Phase 3 Iteration 400 Progress 67%
## Phase 3 Iteration 500 Progress 83%
## Phase 3 Iteration 600 Progress 100%
## Parameter values used for simulations
##
## Mean Standard
## value Deviation
##
## Rate parameters:
## 0 Rate parameter NA ( NA )
##
## Other parameters:
## 1. eval outdegree (density) 0.0 ( NA )
## 2. eval indegree - popularity 0.0 ( NA )
## 3. eval outdegree - activity 0.0 ( NA )
## 4. eval XW=>X closure of self$component_1_coDyadCovar 0.1 ( NA )
## 5. eval self$component_2_coDyadCovar 0.0 ( NA )
## 6. eval self$strat_1_coCovar ego 0.0 ( NA )
## 7. eval ind. pop.^(1/0) weighted self$strat_2_coCovar 0.0 ( NA )
## 8. eval self$strat_3_coCovar tot in-alter dist 2 0.0 ( NA )
## 9. eval self$strat_1_coCovar ego x XW=>X closure of self$component_1_coDyadCovar 0.0 ( NA )
## 10. eval ind. pop.^(1/0) weighted self$strat_2_coCovar x self$component_2_coDyadCovar 0.0 ( NA )
## 11. eval self$strat_3_coCovar tot in-alter dist 2 x self$component_2_coDyadCovar 0.0 ( NA )
##
## Simulated means and standard deviations
## 1. Number of ties 143.118 0.323
## 2. Sum of squared indegrees 1707.722 7.435
## 3. Sum of squared outdegrees 1707.722 7.435
## 4. XW=>X closure of self$component_1_coDyadCovar 284.473 1.293
## 5. Sum of ties x self$component_2_coDyadCovar 0.024 0.416
## 6. Sum of outdegrees x self$strat_1_coCovar 0.018 0.772
## 7. indegree pop.^(1/0) weighted self$strat_2_coCovar -0.202 8.490
## 8. self$strat_3_coCovar tot in-alter dist 2 0.367 15.436
## 9. self$strat_1_coCovar ego x XW=>X closure of self$component_1_coDyadCovar 0.073 3.087
## 10. ind. pop.^(1/0) weighted self$strat_2_coCovar x self$component_2_coDyadCovar 0.054 0.945
## 11. self$strat_3_coCovar tot in-alter dist 2 x self$component_2_coDyadCovar 12.445 2.102
##
##
## Simulated statistics are in x$sf
## and simulated dependent variables in x$sims, where x is the created object.
##
## Total of 600 iteration steps.
##
## Covariance matrix of estimates (correlations below diagonal)
##
## 0 0 0 0 0 0 0 0 0 0 0
## NaN 0 0 0 0 0 0 0 0 0 0
## NaN NaN 0 0 0 0 0 0 0 0 0
## NaN NaN NaN 0 0 0 0 0 0 0 0
## NaN NaN NaN NaN 0 0 0 0 0 0 0
## NaN NaN NaN NaN NaN 0 0 0 0 0 0
## NaN NaN NaN NaN NaN NaN 0 0 0 0 0
## NaN NaN NaN NaN NaN NaN NaN 0 0 0 0
## NaN NaN NaN NaN NaN NaN NaN NaN 0 0 0
## NaN NaN NaN NaN NaN NaN NaN NaN NaN 0 0
## NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN 0
##
## Derivative matrix of expected statistics X by parameters:
##
## 0.104 2.400 2.400 0.417 -0.003 -0.002 0.024 0.000 -0.009 -0.006 0.020
## 1.252 28.795 28.795 5.008 -0.034 -0.026 0.286 0.000 -0.104 -0.077 0.236
## 2.400 55.191 55.191 9.598 -0.064 -0.050 0.549 0.000 -0.200 -0.148 0.453
## 0.417 9.598 9.598 1.669 -0.011 -0.009 0.095 0.000 -0.035 -0.026 0.079
## -0.002 -0.041 -0.041 -0.007 0.155 0.006 -0.064 0.000 0.023 0.012 -0.049
## -0.005 -0.126 -0.126 -0.022 -0.003 0.066 -0.724 0.000 0.263 0.010 -0.023
## 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
## 0.000 0.000 0.000 0.000 0.000 0.000 0.000 1.000 0.000 0.000 0.000
## -0.022 -0.503 -0.503 -0.087 -0.012 0.263 -2.898 0.000 1.054 0.040 -0.091
## 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
## 0.006 0.130 0.130 0.023 -0.028 -0.010 0.105 0.000 -0.038 -0.078 0.551
##
## Covariance matrix of X (correlations below diagonal):
##
## 0.105 2.404 2.404 0.418 -0.003 -0.002 0.024 -0.043 -0.009 -0.006 0.020
## 1.000 55.283 55.283 9.614 -0.064 -0.050 0.550 -1.000 -0.200 -0.148 0.453
## 1.000 1.000 55.283 9.614 -0.064 -0.050 0.550 -1.000 -0.200 -0.148 0.453
## 1.000 1.000 1.000 1.672 -0.011 -0.009 0.096 -0.174 -0.035 -0.026 0.079
## -0.021 -0.021 -0.021 -0.021 0.173 -0.029 0.323 -0.587 -0.117 0.005 -0.036
## -0.009 -0.009 -0.009 -0.009 -0.091 0.596 -6.552 11.913 2.383 0.088 -0.197
## 0.009 0.009 0.009 0.009 0.091 -1.000 72.074 -131.044 -26.209 -0.969 2.166
## -0.009 -0.009 -0.009 -0.009 -0.091 1.000 -1.000 238.263 47.653 1.763 -3.938
## -0.009 -0.009 -0.009 -0.009 -0.091 1.000 -1.000 1.000 9.531 0.353 -0.788
## -0.021 -0.021 -0.021 -0.021 0.013 0.121 -0.121 0.121 0.121 0.892 -1.892
## 0.029 0.029 0.029 0.029 -0.042 -0.121 0.121 -0.121 -0.121 -0.953 4.420
##
##
##
## Simulated Decision Chain Summary:
##
## dv_type dv_type_bin dv_varname id_from
## Length:600 Min. :0 Length:600 Min. : 1.000
## Class :character 1st Qu.:0 Class :character 1st Qu.: 4.000
## Mode :character Median :0 Mode :character Median : 7.000
## Mean :0 Mean : 6.665
## 3rd Qu.:0 3rd Qu.:10.000
## Max. :0 Max. :12.000
## id_to beh_difference reciprocal_rate LogOptionSetProb
## Min. : 1.000 Min. :0 Min. :0.08333 Min. :-2.485
## 1st Qu.: 4.000 1st Qu.:0 1st Qu.:0.08333 1st Qu.:-2.485
## Median : 7.000 Median :0 Median :0.08333 Median :-2.485
## Mean : 7.245 Mean :0 Mean :0.08333 Mean :-2.485
## 3rd Qu.:11.000 3rd Qu.:0 3rd Qu.:0.08333 3rd Qu.:-2.485
## Max. :13.000 Max. :0 Max. :0.08333 Max. :-2.485
## LogChoiceProb diagonal stability tie_change
## Min. :-2.602 Length:600 Mode :logical Mode :logical
## 1st Qu.:-2.602 Class :character FALSE:529 FALSE:71
## Median :-2.602 Mode :character TRUE :71 TRUE :529
## Mean :-2.555
## 3rd Qu.:-2.602
## Max. :-2.202
## chain_step_id
## Min. : 1.0
## 1st Qu.:150.8
## Median :300.5
## Mean :300.4
## 3rd Qu.:450.2
## Max. :600.0
## [1] 600 13
## dv_type dv_type_bin dv_varname id_from id_to beh_difference
## 1 Network 0 self$bipartite_rsienaDV 11 11 0
## 2 Network 0 self$bipartite_rsienaDV 4 7 0
## 3 Network 0 self$bipartite_rsienaDV 12 1 0
## 4 Network 0 self$bipartite_rsienaDV 9 1 0
## 5 Network 0 self$bipartite_rsienaDV 6 6 0
## 6 Network 0 self$bipartite_rsienaDV 3 13 0
## 7 Network 0 self$bipartite_rsienaDV 9 9 0
## 8 Network 0 self$bipartite_rsienaDV 9 8 0
## 9 Network 0 self$bipartite_rsienaDV 1 3 0
## 10 Network 0 self$bipartite_rsienaDV 5 5 0
## 11 Network 0 self$bipartite_rsienaDV 2 11 0
## 12 Network 0 self$bipartite_rsienaDV 4 5 0
## 13 Network 0 self$bipartite_rsienaDV 8 13 0
## 14 Network 0 self$bipartite_rsienaDV 4 3 0
## 15 Network 0 self$bipartite_rsienaDV 6 10 0
## 16 Network 0 self$bipartite_rsienaDV 6 4 0
## 17 Network 0 self$bipartite_rsienaDV 4 13 0
## 18 Network 0 self$bipartite_rsienaDV 12 3 0
## 19 Network 0 self$bipartite_rsienaDV 12 10 0
## 20 Network 0 self$bipartite_rsienaDV 5 5 0
## 21 Network 0 self$bipartite_rsienaDV 8 13 0
## 22 Network 0 self$bipartite_rsienaDV 7 3 0
## 23 Network 0 self$bipartite_rsienaDV 1 2 0
## 24 Network 0 self$bipartite_rsienaDV 10 7 0
## 25 Network 0 self$bipartite_rsienaDV 1 13 0
## 26 Network 0 self$bipartite_rsienaDV 1 9 0
## 27 Network 0 self$bipartite_rsienaDV 7 10 0
## 28 Network 0 self$bipartite_rsienaDV 2 6 0
## 29 Network 0 self$bipartite_rsienaDV 8 13 0
## 30 Network 0 self$bipartite_rsienaDV 7 13 0
## 31 Network 0 self$bipartite_rsienaDV 11 4 0
## 32 Network 0 self$bipartite_rsienaDV 10 6 0
## 33 Network 0 self$bipartite_rsienaDV 11 13 0
## 34 Network 0 self$bipartite_rsienaDV 1 5 0
## 35 Network 0 self$bipartite_rsienaDV 7 2 0
## 36 Network 0 self$bipartite_rsienaDV 9 11 0
## 37 Network 0 self$bipartite_rsienaDV 10 1 0
## 38 Network 0 self$bipartite_rsienaDV 10 9 0
## 39 Network 0 self$bipartite_rsienaDV 3 2 0
## 40 Network 0 self$bipartite_rsienaDV 7 10 0
## 41 Network 0 self$bipartite_rsienaDV 12 13 0
## 42 Network 0 self$bipartite_rsienaDV 7 11 0
## 43 Network 0 self$bipartite_rsienaDV 3 11 0
## 44 Network 0 self$bipartite_rsienaDV 6 12 0
## 45 Network 0 self$bipartite_rsienaDV 9 9 0
## 46 Network 0 self$bipartite_rsienaDV 6 13 0
## 47 Network 0 self$bipartite_rsienaDV 11 6 0
## 48 Network 0 self$bipartite_rsienaDV 5 11 0
## 49 Network 0 self$bipartite_rsienaDV 12 11 0
## 50 Network 0 self$bipartite_rsienaDV 3 6 0
## 51 Network 0 self$bipartite_rsienaDV 4 13 0
## 52 Network 0 self$bipartite_rsienaDV 5 13 0
## 53 Network 0 self$bipartite_rsienaDV 2 11 0
## 54 Network 0 self$bipartite_rsienaDV 12 1 0
## 55 Network 0 self$bipartite_rsienaDV 10 4 0
## 56 Network 0 self$bipartite_rsienaDV 2 7 0
## 57 Network 0 self$bipartite_rsienaDV 10 2 0
## 58 Network 0 self$bipartite_rsienaDV 7 9 0
## 59 Network 0 self$bipartite_rsienaDV 9 6 0
## 60 Network 0 self$bipartite_rsienaDV 12 6 0
## 61 Network 0 self$bipartite_rsienaDV 7 9 0
## 62 Network 0 self$bipartite_rsienaDV 2 2 0
## 63 Network 0 self$bipartite_rsienaDV 7 13 0
## 64 Network 0 self$bipartite_rsienaDV 11 6 0
## 65 Network 0 self$bipartite_rsienaDV 7 7 0
## 66 Network 0 self$bipartite_rsienaDV 9 7 0
## 67 Network 0 self$bipartite_rsienaDV 12 13 0
## 68 Network 0 self$bipartite_rsienaDV 9 13 0
## 69 Network 0 self$bipartite_rsienaDV 5 11 0
## 70 Network 0 self$bipartite_rsienaDV 11 12 0
## 71 Network 0 self$bipartite_rsienaDV 3 2 0
## 72 Network 0 self$bipartite_rsienaDV 10 13 0
## 73 Network 0 self$bipartite_rsienaDV 1 2 0
## 74 Network 0 self$bipartite_rsienaDV 12 10 0
## 75 Network 0 self$bipartite_rsienaDV 4 3 0
## 76 Network 0 self$bipartite_rsienaDV 5 12 0
## 77 Network 0 self$bipartite_rsienaDV 10 2 0
## 78 Network 0 self$bipartite_rsienaDV 4 6 0
## 79 Network 0 self$bipartite_rsienaDV 10 7 0
## 80 Network 0 self$bipartite_rsienaDV 9 12 0
## 81 Network 0 self$bipartite_rsienaDV 10 3 0
## 82 Network 0 self$bipartite_rsienaDV 1 1 0
## 83 Network 0 self$bipartite_rsienaDV 9 9 0
## 84 Network 0 self$bipartite_rsienaDV 9 3 0
## 85 Network 0 self$bipartite_rsienaDV 5 6 0
## 86 Network 0 self$bipartite_rsienaDV 11 8 0
## 87 Network 0 self$bipartite_rsienaDV 4 12 0
## 88 Network 0 self$bipartite_rsienaDV 9 9 0
## 89 Network 0 self$bipartite_rsienaDV 5 13 0
## 90 Network 0 self$bipartite_rsienaDV 1 3 0
## 91 Network 0 self$bipartite_rsienaDV 9 10 0
## 92 Network 0 self$bipartite_rsienaDV 9 7 0
## 93 Network 0 self$bipartite_rsienaDV 11 12 0
## 94 Network 0 self$bipartite_rsienaDV 8 11 0
## 95 Network 0 self$bipartite_rsienaDV 9 9 0
## 96 Network 0 self$bipartite_rsienaDV 8 8 0
## 97 Network 0 self$bipartite_rsienaDV 10 3 0
## 98 Network 0 self$bipartite_rsienaDV 6 4 0
## 99 Network 0 self$bipartite_rsienaDV 9 12 0
## 100 Network 0 self$bipartite_rsienaDV 10 8 0
## 101 Network 0 self$bipartite_rsienaDV 10 13 0
## 102 Network 0 self$bipartite_rsienaDV 8 6 0
## 103 Network 0 self$bipartite_rsienaDV 6 10 0
## 104 Network 0 self$bipartite_rsienaDV 4 10 0
## 105 Network 0 self$bipartite_rsienaDV 11 9 0
## 106 Network 0 self$bipartite_rsienaDV 11 1 0
## 107 Network 0 self$bipartite_rsienaDV 11 11 0
## 108 Network 0 self$bipartite_rsienaDV 4 3 0
## 109 Network 0 self$bipartite_rsienaDV 5 7 0
## 110 Network 0 self$bipartite_rsienaDV 1 7 0
## 111 Network 0 self$bipartite_rsienaDV 3 9 0
## 112 Network 0 self$bipartite_rsienaDV 11 4 0
## 113 Network 0 self$bipartite_rsienaDV 1 8 0
## 114 Network 0 self$bipartite_rsienaDV 1 1 0
## 115 Network 0 self$bipartite_rsienaDV 10 8 0
## 116 Network 0 self$bipartite_rsienaDV 6 2 0
## 117 Network 0 self$bipartite_rsienaDV 4 3 0
## 118 Network 0 self$bipartite_rsienaDV 5 12 0
## 119 Network 0 self$bipartite_rsienaDV 8 1 0
## 120 Network 0 self$bipartite_rsienaDV 4 1 0
## 121 Network 0 self$bipartite_rsienaDV 1 12 0
## 122 Network 0 self$bipartite_rsienaDV 2 11 0
## 123 Network 0 self$bipartite_rsienaDV 1 10 0
## 124 Network 0 self$bipartite_rsienaDV 1 13 0
## 125 Network 0 self$bipartite_rsienaDV 10 7 0
## 126 Network 0 self$bipartite_rsienaDV 12 4 0
## 127 Network 0 self$bipartite_rsienaDV 2 8 0
## 128 Network 0 self$bipartite_rsienaDV 7 6 0
## 129 Network 0 self$bipartite_rsienaDV 5 11 0
## 130 Network 0 self$bipartite_rsienaDV 4 6 0
## 131 Network 0 self$bipartite_rsienaDV 8 4 0
## 132 Network 0 self$bipartite_rsienaDV 9 11 0
## 133 Network 0 self$bipartite_rsienaDV 2 4 0
## 134 Network 0 self$bipartite_rsienaDV 4 8 0
## 135 Network 0 self$bipartite_rsienaDV 8 2 0
## 136 Network 0 self$bipartite_rsienaDV 10 12 0
## 137 Network 0 self$bipartite_rsienaDV 10 11 0
## 138 Network 0 self$bipartite_rsienaDV 11 13 0
## 139 Network 0 self$bipartite_rsienaDV 11 2 0
## 140 Network 0 self$bipartite_rsienaDV 5 11 0
## 141 Network 0 self$bipartite_rsienaDV 5 5 0
## 142 Network 0 self$bipartite_rsienaDV 4 10 0
## 143 Network 0 self$bipartite_rsienaDV 10 11 0
## 144 Network 0 self$bipartite_rsienaDV 11 9 0
## 145 Network 0 self$bipartite_rsienaDV 7 13 0
## 146 Network 0 self$bipartite_rsienaDV 6 5 0
## 147 Network 0 self$bipartite_rsienaDV 8 10 0
## 148 Network 0 self$bipartite_rsienaDV 2 13 0
## 149 Network 0 self$bipartite_rsienaDV 5 4 0
## 150 Network 0 self$bipartite_rsienaDV 3 8 0
## 151 Network 0 self$bipartite_rsienaDV 7 1 0
## 152 Network 0 self$bipartite_rsienaDV 8 11 0
## 153 Network 0 self$bipartite_rsienaDV 11 6 0
## 154 Network 0 self$bipartite_rsienaDV 3 2 0
## 155 Network 0 self$bipartite_rsienaDV 5 1 0
## 156 Network 0 self$bipartite_rsienaDV 7 10 0
## 157 Network 0 self$bipartite_rsienaDV 4 13 0
## 158 Network 0 self$bipartite_rsienaDV 9 3 0
## 159 Network 0 self$bipartite_rsienaDV 8 8 0
## 160 Network 0 self$bipartite_rsienaDV 11 4 0
## 161 Network 0 self$bipartite_rsienaDV 7 5 0
## 162 Network 0 self$bipartite_rsienaDV 3 5 0
## 163 Network 0 self$bipartite_rsienaDV 9 3 0
## 164 Network 0 self$bipartite_rsienaDV 7 2 0
## 165 Network 0 self$bipartite_rsienaDV 10 4 0
## 166 Network 0 self$bipartite_rsienaDV 3 13 0
## 167 Network 0 self$bipartite_rsienaDV 10 10 0
## 168 Network 0 self$bipartite_rsienaDV 7 10 0
## 169 Network 0 self$bipartite_rsienaDV 10 12 0
## 170 Network 0 self$bipartite_rsienaDV 7 3 0
## 171 Network 0 self$bipartite_rsienaDV 1 6 0
## 172 Network 0 self$bipartite_rsienaDV 12 3 0
## 173 Network 0 self$bipartite_rsienaDV 11 7 0
## 174 Network 0 self$bipartite_rsienaDV 12 8 0
## 175 Network 0 self$bipartite_rsienaDV 4 1 0
## 176 Network 0 self$bipartite_rsienaDV 6 13 0
## 177 Network 0 self$bipartite_rsienaDV 8 7 0
## 178 Network 0 self$bipartite_rsienaDV 4 12 0
## 179 Network 0 self$bipartite_rsienaDV 9 13 0
## 180 Network 0 self$bipartite_rsienaDV 4 10 0
## 181 Network 0 self$bipartite_rsienaDV 8 13 0
## 182 Network 0 self$bipartite_rsienaDV 2 13 0
## 183 Network 0 self$bipartite_rsienaDV 9 13 0
## 184 Network 0 self$bipartite_rsienaDV 6 11 0
## 185 Network 0 self$bipartite_rsienaDV 8 8 0
## 186 Network 0 self$bipartite_rsienaDV 1 1 0
## 187 Network 0 self$bipartite_rsienaDV 4 10 0
## 188 Network 0 self$bipartite_rsienaDV 12 2 0
## 189 Network 0 self$bipartite_rsienaDV 11 12 0
## 190 Network 0 self$bipartite_rsienaDV 9 12 0
## 191 Network 0 self$bipartite_rsienaDV 11 2 0
## 192 Network 0 self$bipartite_rsienaDV 1 11 0
## 193 Network 0 self$bipartite_rsienaDV 6 9 0
## 194 Network 0 self$bipartite_rsienaDV 6 5 0
## 195 Network 0 self$bipartite_rsienaDV 9 2 0
## 196 Network 0 self$bipartite_rsienaDV 11 5 0
## 197 Network 0 self$bipartite_rsienaDV 12 9 0
## 198 Network 0 self$bipartite_rsienaDV 7 6 0
## 199 Network 0 self$bipartite_rsienaDV 11 3 0
## 200 Network 0 self$bipartite_rsienaDV 5 1 0
## 201 Network 0 self$bipartite_rsienaDV 2 9 0
## 202 Network 0 self$bipartite_rsienaDV 6 2 0
## 203 Network 0 self$bipartite_rsienaDV 7 11 0
## 204 Network 0 self$bipartite_rsienaDV 8 12 0
## 205 Network 0 self$bipartite_rsienaDV 2 6 0
## 206 Network 0 self$bipartite_rsienaDV 12 13 0
## 207 Network 0 self$bipartite_rsienaDV 1 10 0
## 208 Network 0 self$bipartite_rsienaDV 9 13 0
## 209 Network 0 self$bipartite_rsienaDV 6 1 0
## 210 Network 0 self$bipartite_rsienaDV 10 10 0
## 211 Network 0 self$bipartite_rsienaDV 6 8 0
## 212 Network 0 self$bipartite_rsienaDV 12 4 0
## 213 Network 0 self$bipartite_rsienaDV 9 3 0
## 214 Network 0 self$bipartite_rsienaDV 4 13 0
## 215 Network 0 self$bipartite_rsienaDV 2 1 0
## 216 Network 0 self$bipartite_rsienaDV 10 11 0
## 217 Network 0 self$bipartite_rsienaDV 9 9 0
## 218 Network 0 self$bipartite_rsienaDV 11 5 0
## 219 Network 0 self$bipartite_rsienaDV 8 5 0
## 220 Network 0 self$bipartite_rsienaDV 3 10 0
## 221 Network 0 self$bipartite_rsienaDV 6 7 0
## 222 Network 0 self$bipartite_rsienaDV 5 10 0
## 223 Network 0 self$bipartite_rsienaDV 8 2 0
## 224 Network 0 self$bipartite_rsienaDV 2 4 0
## 225 Network 0 self$bipartite_rsienaDV 10 7 0
## 226 Network 0 self$bipartite_rsienaDV 10 2 0
## 227 Network 0 self$bipartite_rsienaDV 2 9 0
## 228 Network 0 self$bipartite_rsienaDV 2 8 0
## 229 Network 0 self$bipartite_rsienaDV 3 1 0
## 230 Network 0 self$bipartite_rsienaDV 3 6 0
## 231 Network 0 self$bipartite_rsienaDV 9 12 0
## 232 Network 0 self$bipartite_rsienaDV 9 4 0
## 233 Network 0 self$bipartite_rsienaDV 7 4 0
## 234 Network 0 self$bipartite_rsienaDV 7 3 0
## 235 Network 0 self$bipartite_rsienaDV 12 13 0
## 236 Network 0 self$bipartite_rsienaDV 3 5 0
## 237 Network 0 self$bipartite_rsienaDV 8 3 0
## 238 Network 0 self$bipartite_rsienaDV 6 11 0
## 239 Network 0 self$bipartite_rsienaDV 8 2 0
## 240 Network 0 self$bipartite_rsienaDV 8 13 0
## 241 Network 0 self$bipartite_rsienaDV 3 13 0
## 242 Network 0 self$bipartite_rsienaDV 10 6 0
## 243 Network 0 self$bipartite_rsienaDV 1 13 0
## 244 Network 0 self$bipartite_rsienaDV 8 5 0
## 245 Network 0 self$bipartite_rsienaDV 5 8 0
## 246 Network 0 self$bipartite_rsienaDV 11 6 0
## 247 Network 0 self$bipartite_rsienaDV 2 3 0
## 248 Network 0 self$bipartite_rsienaDV 1 3 0
## 249 Network 0 self$bipartite_rsienaDV 4 3 0
## 250 Network 0 self$bipartite_rsienaDV 10 2 0
## 251 Network 0 self$bipartite_rsienaDV 1 5 0
## 252 Network 0 self$bipartite_rsienaDV 11 3 0
## 253 Network 0 self$bipartite_rsienaDV 9 6 0
## 254 Network 0 self$bipartite_rsienaDV 3 5 0
## 255 Network 0 self$bipartite_rsienaDV 5 2 0
## 256 Network 0 self$bipartite_rsienaDV 5 8 0
## 257 Network 0 self$bipartite_rsienaDV 4 3 0
## 258 Network 0 self$bipartite_rsienaDV 6 12 0
## 259 Network 0 self$bipartite_rsienaDV 8 3 0
## 260 Network 0 self$bipartite_rsienaDV 1 5 0
## 261 Network 0 self$bipartite_rsienaDV 8 7 0
## 262 Network 0 self$bipartite_rsienaDV 1 13 0
## 263 Network 0 self$bipartite_rsienaDV 7 11 0
## 264 Network 0 self$bipartite_rsienaDV 4 5 0
## 265 Network 0 self$bipartite_rsienaDV 3 5 0
## 266 Network 0 self$bipartite_rsienaDV 5 7 0
## 267 Network 0 self$bipartite_rsienaDV 6 9 0
## 268 Network 0 self$bipartite_rsienaDV 5 2 0
## 269 Network 0 self$bipartite_rsienaDV 8 13 0
## 270 Network 0 self$bipartite_rsienaDV 12 8 0
## 271 Network 0 self$bipartite_rsienaDV 7 6 0
## 272 Network 0 self$bipartite_rsienaDV 11 2 0
## 273 Network 0 self$bipartite_rsienaDV 5 5 0
## 274 Network 0 self$bipartite_rsienaDV 9 6 0
## 275 Network 0 self$bipartite_rsienaDV 8 4 0
## 276 Network 0 self$bipartite_rsienaDV 11 7 0
## 277 Network 0 self$bipartite_rsienaDV 1 12 0
## 278 Network 0 self$bipartite_rsienaDV 4 3 0
## 279 Network 0 self$bipartite_rsienaDV 12 13 0
## 280 Network 0 self$bipartite_rsienaDV 5 11 0
## 281 Network 0 self$bipartite_rsienaDV 1 10 0
## 282 Network 0 self$bipartite_rsienaDV 10 1 0
## 283 Network 0 self$bipartite_rsienaDV 2 4 0
## 284 Network 0 self$bipartite_rsienaDV 11 7 0
## 285 Network 0 self$bipartite_rsienaDV 8 7 0
## 286 Network 0 self$bipartite_rsienaDV 9 11 0
## 287 Network 0 self$bipartite_rsienaDV 6 1 0
## 288 Network 0 self$bipartite_rsienaDV 9 9 0
## 289 Network 0 self$bipartite_rsienaDV 10 11 0
## 290 Network 0 self$bipartite_rsienaDV 4 7 0
## 291 Network 0 self$bipartite_rsienaDV 8 13 0
## 292 Network 0 self$bipartite_rsienaDV 8 5 0
## 293 Network 0 self$bipartite_rsienaDV 5 7 0
## 294 Network 0 self$bipartite_rsienaDV 6 6 0
## 295 Network 0 self$bipartite_rsienaDV 1 5 0
## 296 Network 0 self$bipartite_rsienaDV 12 13 0
## 297 Network 0 self$bipartite_rsienaDV 1 6 0
## 298 Network 0 self$bipartite_rsienaDV 9 6 0
## 299 Network 0 self$bipartite_rsienaDV 10 6 0
## 300 Network 0 self$bipartite_rsienaDV 7 2 0
## 301 Network 0 self$bipartite_rsienaDV 12 12 0
## 302 Network 0 self$bipartite_rsienaDV 1 6 0
## 303 Network 0 self$bipartite_rsienaDV 1 5 0
## 304 Network 0 self$bipartite_rsienaDV 6 6 0
## 305 Network 0 self$bipartite_rsienaDV 9 12 0
## 306 Network 0 self$bipartite_rsienaDV 12 5 0
## 307 Network 0 self$bipartite_rsienaDV 11 12 0
## 308 Network 0 self$bipartite_rsienaDV 2 4 0
## 309 Network 0 self$bipartite_rsienaDV 7 9 0
## 310 Network 0 self$bipartite_rsienaDV 5 10 0
## 311 Network 0 self$bipartite_rsienaDV 3 12 0
## 312 Network 0 self$bipartite_rsienaDV 5 6 0
## 313 Network 0 self$bipartite_rsienaDV 6 13 0
## 314 Network 0 self$bipartite_rsienaDV 10 2 0
## 315 Network 0 self$bipartite_rsienaDV 7 10 0
## 316 Network 0 self$bipartite_rsienaDV 6 10 0
## 317 Network 0 self$bipartite_rsienaDV 11 9 0
## 318 Network 0 self$bipartite_rsienaDV 6 1 0
## 319 Network 0 self$bipartite_rsienaDV 7 7 0
## 320 Network 0 self$bipartite_rsienaDV 12 2 0
## 321 Network 0 self$bipartite_rsienaDV 4 11 0
## 322 Network 0 self$bipartite_rsienaDV 1 4 0
## 323 Network 0 self$bipartite_rsienaDV 6 11 0
## 324 Network 0 self$bipartite_rsienaDV 1 12 0
## 325 Network 0 self$bipartite_rsienaDV 10 2 0
## 326 Network 0 self$bipartite_rsienaDV 4 12 0
## 327 Network 0 self$bipartite_rsienaDV 12 12 0
## 328 Network 0 self$bipartite_rsienaDV 11 6 0
## 329 Network 0 self$bipartite_rsienaDV 11 3 0
## 330 Network 0 self$bipartite_rsienaDV 4 1 0
## 331 Network 0 self$bipartite_rsienaDV 8 8 0
## 332 Network 0 self$bipartite_rsienaDV 12 4 0
## 333 Network 0 self$bipartite_rsienaDV 2 4 0
## 334 Network 0 self$bipartite_rsienaDV 8 5 0
## 335 Network 0 self$bipartite_rsienaDV 2 5 0
## 336 Network 0 self$bipartite_rsienaDV 8 10 0
## 337 Network 0 self$bipartite_rsienaDV 8 12 0
## 338 Network 0 self$bipartite_rsienaDV 7 1 0
## 339 Network 0 self$bipartite_rsienaDV 9 7 0
## 340 Network 0 self$bipartite_rsienaDV 7 9 0
## 341 Network 0 self$bipartite_rsienaDV 3 3 0
## 342 Network 0 self$bipartite_rsienaDV 12 1 0
## 343 Network 0 self$bipartite_rsienaDV 9 7 0
## 344 Network 0 self$bipartite_rsienaDV 4 1 0
## 345 Network 0 self$bipartite_rsienaDV 11 7 0
## 346 Network 0 self$bipartite_rsienaDV 4 9 0
## 347 Network 0 self$bipartite_rsienaDV 2 8 0
## 348 Network 0 self$bipartite_rsienaDV 7 13 0
## 349 Network 0 self$bipartite_rsienaDV 12 2 0
## 350 Network 0 self$bipartite_rsienaDV 4 4 0
## 351 Network 0 self$bipartite_rsienaDV 9 7 0
## 352 Network 0 self$bipartite_rsienaDV 8 7 0
## 353 Network 0 self$bipartite_rsienaDV 2 5 0
## 354 Network 0 self$bipartite_rsienaDV 3 12 0
## 355 Network 0 self$bipartite_rsienaDV 5 13 0
## 356 Network 0 self$bipartite_rsienaDV 1 13 0
## 357 Network 0 self$bipartite_rsienaDV 6 3 0
## 358 Network 0 self$bipartite_rsienaDV 8 11 0
## 359 Network 0 self$bipartite_rsienaDV 7 3 0
## 360 Network 0 self$bipartite_rsienaDV 4 2 0
## 361 Network 0 self$bipartite_rsienaDV 12 8 0
## 362 Network 0 self$bipartite_rsienaDV 3 9 0
## 363 Network 0 self$bipartite_rsienaDV 1 11 0
## 364 Network 0 self$bipartite_rsienaDV 10 13 0
## 365 Network 0 self$bipartite_rsienaDV 12 13 0
## 366 Network 0 self$bipartite_rsienaDV 7 10 0
## 367 Network 0 self$bipartite_rsienaDV 2 2 0
## 368 Network 0 self$bipartite_rsienaDV 6 7 0
## 369 Network 0 self$bipartite_rsienaDV 5 9 0
## 370 Network 0 self$bipartite_rsienaDV 8 11 0
## 371 Network 0 self$bipartite_rsienaDV 6 5 0
## 372 Network 0 self$bipartite_rsienaDV 9 1 0
## 373 Network 0 self$bipartite_rsienaDV 3 1 0
## 374 Network 0 self$bipartite_rsienaDV 9 4 0
## 375 Network 0 self$bipartite_rsienaDV 12 7 0
## 376 Network 0 self$bipartite_rsienaDV 11 3 0
## 377 Network 0 self$bipartite_rsienaDV 2 13 0
## 378 Network 0 self$bipartite_rsienaDV 10 9 0
## 379 Network 0 self$bipartite_rsienaDV 6 6 0
## 380 Network 0 self$bipartite_rsienaDV 8 6 0
## 381 Network 0 self$bipartite_rsienaDV 2 5 0
## 382 Network 0 self$bipartite_rsienaDV 3 4 0
## 383 Network 0 self$bipartite_rsienaDV 8 5 0
## 384 Network 0 self$bipartite_rsienaDV 1 13 0
## 385 Network 0 self$bipartite_rsienaDV 12 12 0
## 386 Network 0 self$bipartite_rsienaDV 11 2 0
## 387 Network 0 self$bipartite_rsienaDV 6 8 0
## 388 Network 0 self$bipartite_rsienaDV 12 5 0
## 389 Network 0 self$bipartite_rsienaDV 6 7 0
## 390 Network 0 self$bipartite_rsienaDV 2 7 0
## 391 Network 0 self$bipartite_rsienaDV 9 5 0
## 392 Network 0 self$bipartite_rsienaDV 10 2 0
## 393 Network 0 self$bipartite_rsienaDV 12 4 0
## 394 Network 0 self$bipartite_rsienaDV 11 6 0
## 395 Network 0 self$bipartite_rsienaDV 11 10 0
## 396 Network 0 self$bipartite_rsienaDV 12 3 0
## 397 Network 0 self$bipartite_rsienaDV 4 12 0
## 398 Network 0 self$bipartite_rsienaDV 12 1 0
## 399 Network 0 self$bipartite_rsienaDV 12 11 0
## 400 Network 0 self$bipartite_rsienaDV 10 5 0
## 401 Network 0 self$bipartite_rsienaDV 6 13 0
## 402 Network 0 self$bipartite_rsienaDV 6 11 0
## 403 Network 0 self$bipartite_rsienaDV 8 12 0
## 404 Network 0 self$bipartite_rsienaDV 11 1 0
## 405 Network 0 self$bipartite_rsienaDV 6 9 0
## 406 Network 0 self$bipartite_rsienaDV 5 10 0
## 407 Network 0 self$bipartite_rsienaDV 3 4 0
## 408 Network 0 self$bipartite_rsienaDV 4 5 0
## 409 Network 0 self$bipartite_rsienaDV 4 10 0
## 410 Network 0 self$bipartite_rsienaDV 7 13 0
## 411 Network 0 self$bipartite_rsienaDV 4 5 0
## 412 Network 0 self$bipartite_rsienaDV 11 8 0
## 413 Network 0 self$bipartite_rsienaDV 3 7 0
## 414 Network 0 self$bipartite_rsienaDV 12 2 0
## 415 Network 0 self$bipartite_rsienaDV 6 6 0
## 416 Network 0 self$bipartite_rsienaDV 2 7 0
## 417 Network 0 self$bipartite_rsienaDV 8 7 0
## 418 Network 0 self$bipartite_rsienaDV 10 2 0
## 419 Network 0 self$bipartite_rsienaDV 7 12 0
## 420 Network 0 self$bipartite_rsienaDV 9 3 0
## 421 Network 0 self$bipartite_rsienaDV 12 13 0
## 422 Network 0 self$bipartite_rsienaDV 6 5 0
## 423 Network 0 self$bipartite_rsienaDV 9 7 0
## 424 Network 0 self$bipartite_rsienaDV 1 12 0
## 425 Network 0 self$bipartite_rsienaDV 4 11 0
## 426 Network 0 self$bipartite_rsienaDV 8 6 0
## 427 Network 0 self$bipartite_rsienaDV 9 9 0
## 428 Network 0 self$bipartite_rsienaDV 7 4 0
## 429 Network 0 self$bipartite_rsienaDV 9 5 0
## 430 Network 0 self$bipartite_rsienaDV 10 4 0
## 431 Network 0 self$bipartite_rsienaDV 9 12 0
## 432 Network 0 self$bipartite_rsienaDV 10 13 0
## 433 Network 0 self$bipartite_rsienaDV 12 10 0
## 434 Network 0 self$bipartite_rsienaDV 8 13 0
## 435 Network 0 self$bipartite_rsienaDV 6 8 0
## 436 Network 0 self$bipartite_rsienaDV 12 11 0
## 437 Network 0 self$bipartite_rsienaDV 4 6 0
## 438 Network 0 self$bipartite_rsienaDV 9 2 0
## 439 Network 0 self$bipartite_rsienaDV 11 10 0
## 440 Network 0 self$bipartite_rsienaDV 11 10 0
## 441 Network 0 self$bipartite_rsienaDV 6 12 0
## 442 Network 0 self$bipartite_rsienaDV 9 13 0
## 443 Network 0 self$bipartite_rsienaDV 4 5 0
## 444 Network 0 self$bipartite_rsienaDV 10 2 0
## 445 Network 0 self$bipartite_rsienaDV 5 11 0
## 446 Network 0 self$bipartite_rsienaDV 7 5 0
## 447 Network 0 self$bipartite_rsienaDV 2 11 0
## 448 Network 0 self$bipartite_rsienaDV 7 9 0
## 449 Network 0 self$bipartite_rsienaDV 10 4 0
## 450 Network 0 self$bipartite_rsienaDV 12 9 0
## 451 Network 0 self$bipartite_rsienaDV 3 3 0
## 452 Network 0 self$bipartite_rsienaDV 11 4 0
## 453 Network 0 self$bipartite_rsienaDV 5 8 0
## 454 Network 0 self$bipartite_rsienaDV 10 4 0
## 455 Network 0 self$bipartite_rsienaDV 6 10 0
## 456 Network 0 self$bipartite_rsienaDV 10 10 0
## 457 Network 0 self$bipartite_rsienaDV 1 13 0
## 458 Network 0 self$bipartite_rsienaDV 7 1 0
## 459 Network 0 self$bipartite_rsienaDV 9 5 0
## 460 Network 0 self$bipartite_rsienaDV 1 2 0
## 461 Network 0 self$bipartite_rsienaDV 10 10 0
## 462 Network 0 self$bipartite_rsienaDV 12 9 0
## 463 Network 0 self$bipartite_rsienaDV 1 7 0
## 464 Network 0 self$bipartite_rsienaDV 10 4 0
## 465 Network 0 self$bipartite_rsienaDV 8 8 0
## 466 Network 0 self$bipartite_rsienaDV 8 5 0
## 467 Network 0 self$bipartite_rsienaDV 5 8 0
## 468 Network 0 self$bipartite_rsienaDV 3 6 0
## 469 Network 0 self$bipartite_rsienaDV 12 7 0
## 470 Network 0 self$bipartite_rsienaDV 9 1 0
## 471 Network 0 self$bipartite_rsienaDV 2 1 0
## 472 Network 0 self$bipartite_rsienaDV 2 13 0
## 473 Network 0 self$bipartite_rsienaDV 1 2 0
## 474 Network 0 self$bipartite_rsienaDV 12 2 0
## 475 Network 0 self$bipartite_rsienaDV 10 7 0
## 476 Network 0 self$bipartite_rsienaDV 3 4 0
## 477 Network 0 self$bipartite_rsienaDV 8 9 0
## 478 Network 0 self$bipartite_rsienaDV 3 13 0
## 479 Network 0 self$bipartite_rsienaDV 10 2 0
## 480 Network 0 self$bipartite_rsienaDV 8 13 0
## 481 Network 0 self$bipartite_rsienaDV 1 6 0
## 482 Network 0 self$bipartite_rsienaDV 9 4 0
## 483 Network 0 self$bipartite_rsienaDV 11 8 0
## 484 Network 0 self$bipartite_rsienaDV 10 2 0
## 485 Network 0 self$bipartite_rsienaDV 1 4 0
## 486 Network 0 self$bipartite_rsienaDV 10 8 0
## 487 Network 0 self$bipartite_rsienaDV 9 10 0
## 488 Network 0 self$bipartite_rsienaDV 1 11 0
## 489 Network 0 self$bipartite_rsienaDV 6 9 0
## 490 Network 0 self$bipartite_rsienaDV 7 1 0
## 491 Network 0 self$bipartite_rsienaDV 2 5 0
## 492 Network 0 self$bipartite_rsienaDV 2 13 0
## 493 Network 0 self$bipartite_rsienaDV 5 7 0
## 494 Network 0 self$bipartite_rsienaDV 4 6 0
## 495 Network 0 self$bipartite_rsienaDV 1 8 0
## 496 Network 0 self$bipartite_rsienaDV 10 9 0
## 497 Network 0 self$bipartite_rsienaDV 7 12 0
## 498 Network 0 self$bipartite_rsienaDV 5 6 0
## 499 Network 0 self$bipartite_rsienaDV 10 7 0
## 500 Network 0 self$bipartite_rsienaDV 11 4 0
## 501 Network 0 self$bipartite_rsienaDV 5 10 0
## 502 Network 0 self$bipartite_rsienaDV 10 7 0
## 503 Network 0 self$bipartite_rsienaDV 7 6 0
## 504 Network 0 self$bipartite_rsienaDV 10 2 0
## 505 Network 0 self$bipartite_rsienaDV 1 13 0
## 506 Network 0 self$bipartite_rsienaDV 4 7 0
## 507 Network 0 self$bipartite_rsienaDV 11 13 0
## 508 Network 0 self$bipartite_rsienaDV 11 9 0
## 509 Network 0 self$bipartite_rsienaDV 2 10 0
## 510 Network 0 self$bipartite_rsienaDV 7 1 0
## 511 Network 0 self$bipartite_rsienaDV 5 9 0
## 512 Network 0 self$bipartite_rsienaDV 11 6 0
## 513 Network 0 self$bipartite_rsienaDV 1 7 0
## 514 Network 0 self$bipartite_rsienaDV 8 6 0
## 515 Network 0 self$bipartite_rsienaDV 3 7 0
## 516 Network 0 self$bipartite_rsienaDV 10 2 0
## 517 Network 0 self$bipartite_rsienaDV 1 5 0
## 518 Network 0 self$bipartite_rsienaDV 11 4 0
## 519 Network 0 self$bipartite_rsienaDV 2 11 0
## 520 Network 0 self$bipartite_rsienaDV 6 1 0
## 521 Network 0 self$bipartite_rsienaDV 11 6 0
## 522 Network 0 self$bipartite_rsienaDV 9 6 0
## 523 Network 0 self$bipartite_rsienaDV 8 4 0
## 524 Network 0 self$bipartite_rsienaDV 7 6 0
## 525 Network 0 self$bipartite_rsienaDV 4 7 0
## 526 Network 0 self$bipartite_rsienaDV 4 9 0
## 527 Network 0 self$bipartite_rsienaDV 3 12 0
## 528 Network 0 self$bipartite_rsienaDV 5 13 0
## 529 Network 0 self$bipartite_rsienaDV 12 12 0
## 530 Network 0 self$bipartite_rsienaDV 3 3 0
## 531 Network 0 self$bipartite_rsienaDV 3 6 0
## 532 Network 0 self$bipartite_rsienaDV 8 5 0
## 533 Network 0 self$bipartite_rsienaDV 6 5 0
## 534 Network 0 self$bipartite_rsienaDV 11 12 0
## 535 Network 0 self$bipartite_rsienaDV 10 7 0
## 536 Network 0 self$bipartite_rsienaDV 7 13 0
## 537 Network 0 self$bipartite_rsienaDV 11 11 0
## 538 Network 0 self$bipartite_rsienaDV 3 3 0
## 539 Network 0 self$bipartite_rsienaDV 12 6 0
## 540 Network 0 self$bipartite_rsienaDV 1 10 0
## 541 Network 0 self$bipartite_rsienaDV 11 6 0
## 542 Network 0 self$bipartite_rsienaDV 2 2 0
## 543 Network 0 self$bipartite_rsienaDV 5 6 0
## 544 Network 0 self$bipartite_rsienaDV 3 13 0
## 545 Network 0 self$bipartite_rsienaDV 11 13 0
## 546 Network 0 self$bipartite_rsienaDV 1 8 0
## 547 Network 0 self$bipartite_rsienaDV 6 9 0
## 548 Network 0 self$bipartite_rsienaDV 12 9 0
## 549 Network 0 self$bipartite_rsienaDV 11 3 0
## 550 Network 0 self$bipartite_rsienaDV 5 13 0
## 551 Network 0 self$bipartite_rsienaDV 2 3 0
## 552 Network 0 self$bipartite_rsienaDV 9 9 0
## 553 Network 0 self$bipartite_rsienaDV 12 6 0
## 554 Network 0 self$bipartite_rsienaDV 4 13 0
## 555 Network 0 self$bipartite_rsienaDV 9 2 0
## 556 Network 0 self$bipartite_rsienaDV 11 10 0
## 557 Network 0 self$bipartite_rsienaDV 1 9 0
## 558 Network 0 self$bipartite_rsienaDV 2 10 0
## 559 Network 0 self$bipartite_rsienaDV 1 13 0
## 560 Network 0 self$bipartite_rsienaDV 1 13 0
## 561 Network 0 self$bipartite_rsienaDV 2 5 0
## 562 Network 0 self$bipartite_rsienaDV 9 7 0
## 563 Network 0 self$bipartite_rsienaDV 2 9 0
## 564 Network 0 self$bipartite_rsienaDV 6 11 0
## 565 Network 0 self$bipartite_rsienaDV 6 1 0
## 566 Network 0 self$bipartite_rsienaDV 4 7 0
## 567 Network 0 self$bipartite_rsienaDV 10 3 0
## 568 Network 0 self$bipartite_rsienaDV 8 6 0
## 569 Network 0 self$bipartite_rsienaDV 3 9 0
## 570 Network 0 self$bipartite_rsienaDV 3 4 0
## 571 Network 0 self$bipartite_rsienaDV 4 2 0
## 572 Network 0 self$bipartite_rsienaDV 8 2 0
## 573 Network 0 self$bipartite_rsienaDV 4 7 0
## 574 Network 0 self$bipartite_rsienaDV 1 2 0
## 575 Network 0 self$bipartite_rsienaDV 1 10 0
## 576 Network 0 self$bipartite_rsienaDV 3 4 0
## 577 Network 0 self$bipartite_rsienaDV 4 10 0
## 578 Network 0 self$bipartite_rsienaDV 7 9 0
## 579 Network 0 self$bipartite_rsienaDV 5 9 0
## 580 Network 0 self$bipartite_rsienaDV 4 5 0
## 581 Network 0 self$bipartite_rsienaDV 12 6 0
## 582 Network 0 self$bipartite_rsienaDV 1 1 0
## 583 Network 0 self$bipartite_rsienaDV 5 5 0
## 584 Network 0 self$bipartite_rsienaDV 10 12 0
## 585 Network 0 self$bipartite_rsienaDV 5 2 0
## 586 Network 0 self$bipartite_rsienaDV 6 3 0
## 587 Network 0 self$bipartite_rsienaDV 2 1 0
## 588 Network 0 self$bipartite_rsienaDV 2 3 0
## 589 Network 0 self$bipartite_rsienaDV 2 11 0
## 590 Network 0 self$bipartite_rsienaDV 11 10 0
## 591 Network 0 self$bipartite_rsienaDV 6 10 0
## 592 Network 0 self$bipartite_rsienaDV 10 10 0
## 593 Network 0 self$bipartite_rsienaDV 5 2 0
## 594 Network 0 self$bipartite_rsienaDV 3 10 0
## 595 Network 0 self$bipartite_rsienaDV 3 10 0
## 596 Network 0 self$bipartite_rsienaDV 2 5 0
## 597 Network 0 self$bipartite_rsienaDV 6 11 0
## 598 Network 0 self$bipartite_rsienaDV 1 13 0
## 599 Network 0 self$bipartite_rsienaDV 4 10 0
## 600 Network 0 self$bipartite_rsienaDV 3 3 0
## reciprocal_rate LogOptionSetProb LogChoiceProb diagonal stability
## 1 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 2 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 3 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 4 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 5 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 6 0.08333333 -2.484907 -2.202084 FALSE TRUE
## 7 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 8 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 9 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 10 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 11 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 12 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 13 0.08333333 -2.484907 -2.202084 FALSE TRUE
## 14 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 15 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 16 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 17 0.08333333 -2.484907 -2.202084 FALSE TRUE
## 18 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 19 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 20 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 21 0.08333333 -2.484907 -2.202084 FALSE TRUE
## 22 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 23 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 24 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 25 0.08333333 -2.484907 -2.202084 FALSE TRUE
## 26 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 27 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 28 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 29 0.08333333 -2.484907 -2.202084 FALSE TRUE
## 30 0.08333333 -2.484907 -2.202084 FALSE TRUE
## 31 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 32 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 33 0.08333333 -2.484907 -2.202084 FALSE TRUE
## 34 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 35 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 36 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 37 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 38 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 39 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 40 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 41 0.08333333 -2.484907 -2.202084 FALSE TRUE
## 42 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 43 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 44 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 45 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 46 0.08333333 -2.484907 -2.202084 FALSE TRUE
## 47 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 48 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 49 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 50 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 51 0.08333333 -2.484907 -2.202084 FALSE TRUE
## 52 0.08333333 -2.484907 -2.202084 FALSE TRUE
## 53 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 54 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 55 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 56 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 57 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 58 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 59 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 60 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 61 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 62 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 63 0.08333333 -2.484907 -2.202084 FALSE TRUE
## 64 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 65 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 66 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 67 0.08333333 -2.484907 -2.202084 FALSE TRUE
## 68 0.08333333 -2.484907 -2.202084 FALSE TRUE
## 69 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 70 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 71 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 72 0.08333333 -2.484907 -2.202084 FALSE TRUE
## 73 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 74 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 75 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 76 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 77 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 78 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 79 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 80 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 81 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 82 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 83 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 84 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 85 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 86 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 87 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 88 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 89 0.08333333 -2.484907 -2.202084 FALSE TRUE
## 90 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 91 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 92 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 93 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 94 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 95 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 96 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 97 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 98 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 99 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 100 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 101 0.08333333 -2.484907 -2.202084 FALSE TRUE
## 102 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 103 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 104 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 105 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 106 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 107 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 108 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 109 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 110 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 111 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 112 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 113 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 114 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 115 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 116 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 117 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 118 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 119 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 120 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 121 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 122 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 123 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 124 0.08333333 -2.484907 -2.202084 FALSE TRUE
## 125 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 126 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 127 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 128 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 129 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 130 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 131 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 132 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 133 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 134 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 135 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 136 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 137 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 138 0.08333333 -2.484907 -2.202084 FALSE TRUE
## 139 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 140 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 141 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 142 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 143 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 144 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 145 0.08333333 -2.484907 -2.202084 FALSE TRUE
## 146 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 147 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 148 0.08333333 -2.484907 -2.202084 FALSE TRUE
## 149 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 150 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 151 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 152 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 153 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 154 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 155 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 156 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 157 0.08333333 -2.484907 -2.202084 FALSE TRUE
## 158 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 159 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 160 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 161 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 162 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 163 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 164 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 165 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 166 0.08333333 -2.484907 -2.202084 FALSE TRUE
## 167 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 168 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 169 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 170 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 171 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 172 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 173 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 174 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 175 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 176 0.08333333 -2.484907 -2.202084 FALSE TRUE
## 177 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 178 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 179 0.08333333 -2.484907 -2.202084 FALSE TRUE
## 180 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 181 0.08333333 -2.484907 -2.202084 FALSE TRUE
## 182 0.08333333 -2.484907 -2.202084 FALSE TRUE
## 183 0.08333333 -2.484907 -2.202084 FALSE TRUE
## 184 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 185 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 186 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 187 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 188 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 189 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 190 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 191 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 192 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 193 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 194 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 195 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 196 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 197 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 198 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 199 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 200 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 201 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 202 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 203 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 204 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 205 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 206 0.08333333 -2.484907 -2.202084 FALSE TRUE
## 207 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 208 0.08333333 -2.484907 -2.202084 FALSE TRUE
## 209 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 210 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 211 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 212 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 213 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 214 0.08333333 -2.484907 -2.202084 FALSE TRUE
## 215 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 216 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 217 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 218 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 219 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 220 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 221 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 222 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 223 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 224 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 225 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 226 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 227 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 228 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 229 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 230 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 231 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 232 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 233 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 234 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 235 0.08333333 -2.484907 -2.202084 FALSE TRUE
## 236 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 237 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 238 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 239 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 240 0.08333333 -2.484907 -2.202084 FALSE TRUE
## 241 0.08333333 -2.484907 -2.202084 FALSE TRUE
## 242 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 243 0.08333333 -2.484907 -2.202084 FALSE TRUE
## 244 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 245 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 246 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 247 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 248 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 249 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 250 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 251 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 252 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 253 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 254 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 255 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 256 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 257 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 258 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 259 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 260 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 261 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 262 0.08333333 -2.484907 -2.202084 FALSE TRUE
## 263 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 264 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 265 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 266 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 267 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 268 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 269 0.08333333 -2.484907 -2.202084 FALSE TRUE
## 270 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 271 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 272 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 273 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 274 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 275 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 276 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 277 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 278 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 279 0.08333333 -2.484907 -2.202084 FALSE TRUE
## 280 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 281 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 282 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 283 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 284 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 285 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 286 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 287 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 288 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 289 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 290 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 291 0.08333333 -2.484907 -2.202084 FALSE TRUE
## 292 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 293 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 294 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 295 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 296 0.08333333 -2.484907 -2.202084 FALSE TRUE
## 297 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 298 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 299 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 300 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 301 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 302 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 303 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 304 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 305 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 306 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 307 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 308 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 309 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 310 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 311 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 312 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 313 0.08333333 -2.484907 -2.202084 FALSE TRUE
## 314 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 315 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 316 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 317 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 318 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 319 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 320 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 321 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 322 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 323 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 324 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 325 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 326 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 327 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 328 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 329 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 330 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 331 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 332 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 333 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 334 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 335 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 336 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 337 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 338 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 339 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 340 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 341 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 342 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 343 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 344 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 345 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 346 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 347 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 348 0.08333333 -2.484907 -2.202084 FALSE TRUE
## 349 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 350 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 351 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 352 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 353 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 354 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 355 0.08333333 -2.484907 -2.202084 FALSE TRUE
## 356 0.08333333 -2.484907 -2.202084 FALSE TRUE
## 357 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 358 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 359 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 360 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 361 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 362 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 363 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 364 0.08333333 -2.484907 -2.202084 FALSE TRUE
## 365 0.08333333 -2.484907 -2.202084 FALSE TRUE
## 366 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 367 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 368 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 369 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 370 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 371 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 372 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 373 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 374 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 375 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 376 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 377 0.08333333 -2.484907 -2.202084 FALSE TRUE
## 378 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 379 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 380 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 381 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 382 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 383 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 384 0.08333333 -2.484907 -2.202084 FALSE TRUE
## 385 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 386 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 387 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 388 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 389 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 390 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 391 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 392 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 393 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 394 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 395 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 396 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 397 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 398 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 399 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 400 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 401 0.08333333 -2.484907 -2.202084 FALSE TRUE
## 402 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 403 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 404 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 405 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 406 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 407 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 408 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 409 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 410 0.08333333 -2.484907 -2.202084 FALSE TRUE
## 411 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 412 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 413 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 414 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 415 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 416 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 417 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 418 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 419 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 420 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 421 0.08333333 -2.484907 -2.202084 FALSE TRUE
## 422 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 423 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 424 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 425 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 426 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 427 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 428 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 429 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 430 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 431 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 432 0.08333333 -2.484907 -2.202084 FALSE TRUE
## 433 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 434 0.08333333 -2.484907 -2.202084 FALSE TRUE
## 435 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 436 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 437 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 438 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 439 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 440 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 441 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 442 0.08333333 -2.484907 -2.202084 FALSE TRUE
## 443 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 444 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 445 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 446 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 447 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 448 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 449 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 450 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 451 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 452 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 453 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 454 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 455 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 456 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 457 0.08333333 -2.484907 -2.202084 FALSE TRUE
## 458 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 459 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 460 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 461 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 462 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 463 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 464 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 465 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 466 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 467 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 468 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 469 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 470 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 471 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 472 0.08333333 -2.484907 -2.202084 FALSE TRUE
## 473 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 474 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 475 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 476 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 477 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 478 0.08333333 -2.484907 -2.202084 FALSE TRUE
## 479 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 480 0.08333333 -2.484907 -2.202084 FALSE TRUE
## 481 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 482 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 483 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 484 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 485 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 486 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 487 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 488 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 489 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 490 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 491 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 492 0.08333333 -2.484907 -2.202084 FALSE TRUE
## 493 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 494 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 495 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 496 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 497 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 498 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 499 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 500 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 501 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 502 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 503 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 504 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 505 0.08333333 -2.484907 -2.202084 FALSE TRUE
## 506 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 507 0.08333333 -2.484907 -2.202084 FALSE TRUE
## 508 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 509 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 510 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 511 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 512 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 513 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 514 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 515 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 516 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 517 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 518 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 519 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 520 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 521 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 522 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 523 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 524 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 525 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 526 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 527 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 528 0.08333333 -2.484907 -2.202084 FALSE TRUE
## 529 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 530 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 531 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 532 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 533 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 534 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 535 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 536 0.08333333 -2.484907 -2.202084 FALSE TRUE
## 537 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 538 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 539 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 540 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 541 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 542 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 543 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 544 0.08333333 -2.484907 -2.202084 FALSE TRUE
## 545 0.08333333 -2.484907 -2.202084 FALSE TRUE
## 546 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 547 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 548 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 549 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 550 0.08333333 -2.484907 -2.202084 FALSE TRUE
## 551 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 552 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 553 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 554 0.08333333 -2.484907 -2.202084 FALSE TRUE
## 555 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 556 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 557 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 558 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 559 0.08333333 -2.484907 -2.202084 FALSE TRUE
## 560 0.08333333 -2.484907 -2.202084 FALSE TRUE
## 561 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 562 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 563 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 564 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 565 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 566 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 567 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 568 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 569 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 570 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 571 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 572 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 573 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 574 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 575 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 576 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 577 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 578 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 579 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 580 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 581 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 582 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 583 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 584 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 585 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 586 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 587 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 588 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 589 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 590 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 591 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 592 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 593 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 594 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 595 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 596 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 597 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 598 0.08333333 -2.484907 -2.202084 FALSE TRUE
## 599 0.08333333 -2.484907 -2.602084 FALSE FALSE
## 600 0.08333333 -2.484907 -2.602084 FALSE FALSE
## tie_change chain_step_id
## 1 TRUE 1
## 2 TRUE 2
## 3 TRUE 3
## 4 TRUE 4
## 5 TRUE 5
## 6 FALSE 5
## 7 TRUE 7
## 8 TRUE 8
## 9 TRUE 9
## 10 TRUE 10
## 11 TRUE 11
## 12 TRUE 12
## 13 FALSE 12
## 14 TRUE 14
## 15 TRUE 15
## 16 TRUE 16
## 17 FALSE 16
## 18 TRUE 18
## 19 TRUE 19
## 20 TRUE 20
## 21 FALSE 20
## 22 TRUE 22
## 23 TRUE 23
## 24 TRUE 24
## 25 FALSE 24
## 26 TRUE 26
## 27 TRUE 27
## 28 TRUE 28
## 29 FALSE 28
## 30 FALSE 28
## 31 TRUE 31
## 32 TRUE 32
## 33 FALSE 32
## 34 TRUE 34
## 35 TRUE 35
## 36 TRUE 36
## 37 TRUE 37
## 38 TRUE 38
## 39 TRUE 39
## 40 TRUE 40
## 41 FALSE 40
## 42 TRUE 42
## 43 TRUE 43
## 44 TRUE 44
## 45 TRUE 45
## 46 FALSE 45
## 47 TRUE 47
## 48 TRUE 48
## 49 TRUE 49
## 50 TRUE 50
## 51 FALSE 50
## 52 FALSE 50
## 53 TRUE 53
## 54 TRUE 54
## 55 TRUE 55
## 56 TRUE 56
## 57 TRUE 57
## 58 TRUE 58
## 59 TRUE 59
## 60 TRUE 60
## 61 TRUE 61
## 62 TRUE 62
## 63 FALSE 62
## 64 TRUE 64
## 65 TRUE 65
## 66 TRUE 66
## 67 FALSE 66
## 68 FALSE 66
## 69 TRUE 69
## 70 TRUE 70
## 71 TRUE 71
## 72 FALSE 71
## 73 TRUE 73
## 74 TRUE 74
## 75 TRUE 75
## 76 TRUE 76
## 77 TRUE 77
## 78 TRUE 78
## 79 TRUE 79
## 80 TRUE 80
## 81 TRUE 81
## 82 TRUE 82
## 83 TRUE 83
## 84 TRUE 84
## 85 TRUE 85
## 86 TRUE 86
## 87 TRUE 87
## 88 TRUE 88
## 89 FALSE 88
## 90 TRUE 90
## 91 TRUE 91
## 92 TRUE 92
## 93 TRUE 93
## 94 TRUE 94
## 95 TRUE 95
## 96 TRUE 96
## 97 TRUE 97
## 98 TRUE 98
## 99 TRUE 99
## 100 TRUE 100
## 101 FALSE 100
## 102 TRUE 102
## 103 TRUE 103
## 104 TRUE 104
## 105 TRUE 105
## 106 TRUE 106
## 107 TRUE 107
## 108 TRUE 108
## 109 TRUE 109
## 110 TRUE 110
## 111 TRUE 111
## 112 TRUE 112
## 113 TRUE 113
## 114 TRUE 114
## 115 TRUE 115
## 116 TRUE 116
## 117 TRUE 117
## 118 TRUE 118
## 119 TRUE 119
## 120 TRUE 120
## 121 TRUE 121
## 122 TRUE 122
## 123 TRUE 123
## 124 FALSE 123
## 125 TRUE 125
## 126 TRUE 126
## 127 TRUE 127
## 128 TRUE 128
## 129 TRUE 129
## 130 TRUE 130
## 131 TRUE 131
## 132 TRUE 132
## 133 TRUE 133
## 134 TRUE 134
## 135 TRUE 135
## 136 TRUE 136
## 137 TRUE 137
## 138 FALSE 137
## 139 TRUE 139
## 140 TRUE 140
## 141 TRUE 141
## 142 TRUE 142
## 143 TRUE 143
## 144 TRUE 144
## 145 FALSE 144
## 146 TRUE 146
## 147 TRUE 147
## 148 FALSE 147
## 149 TRUE 149
## 150 TRUE 150
## 151 TRUE 151
## 152 TRUE 152
## 153 TRUE 153
## 154 TRUE 154
## 155 TRUE 155
## 156 TRUE 156
## 157 FALSE 156
## 158 TRUE 158
## 159 TRUE 159
## 160 TRUE 160
## 161 TRUE 161
## 162 TRUE 162
## 163 TRUE 163
## 164 TRUE 164
## 165 TRUE 165
## 166 FALSE 165
## 167 TRUE 167
## 168 TRUE 168
## 169 TRUE 169
## 170 TRUE 170
## 171 TRUE 171
## 172 TRUE 172
## 173 TRUE 173
## 174 TRUE 174
## 175 TRUE 175
## 176 FALSE 175
## 177 TRUE 177
## 178 TRUE 178
## 179 FALSE 178
## 180 TRUE 180
## 181 FALSE 180
## 182 FALSE 180
## 183 FALSE 180
## 184 TRUE 184
## 185 TRUE 185
## 186 TRUE 186
## 187 TRUE 187
## 188 TRUE 188
## 189 TRUE 189
## 190 TRUE 190
## 191 TRUE 191
## 192 TRUE 192
## 193 TRUE 193
## 194 TRUE 194
## 195 TRUE 195
## 196 TRUE 196
## 197 TRUE 197
## 198 TRUE 198
## 199 TRUE 199
## 200 TRUE 200
## 201 TRUE 201
## 202 TRUE 202
## 203 TRUE 203
## 204 TRUE 204
## 205 TRUE 205
## 206 FALSE 205
## 207 TRUE 207
## 208 FALSE 207
## 209 TRUE 209
## 210 TRUE 210
## 211 TRUE 211
## 212 TRUE 212
## 213 TRUE 213
## 214 FALSE 213
## 215 TRUE 215
## 216 TRUE 216
## 217 TRUE 217
## 218 TRUE 218
## 219 TRUE 219
## 220 TRUE 220
## 221 TRUE 221
## 222 TRUE 222
## 223 TRUE 223
## 224 TRUE 224
## 225 TRUE 225
## 226 TRUE 226
## 227 TRUE 227
## 228 TRUE 228
## 229 TRUE 229
## 230 TRUE 230
## 231 TRUE 231
## 232 TRUE 232
## 233 TRUE 233
## 234 TRUE 234
## 235 FALSE 234
## 236 TRUE 236
## 237 TRUE 237
## 238 TRUE 238
## 239 TRUE 239
## 240 FALSE 239
## 241 FALSE 239
## 242 TRUE 242
## 243 FALSE 242
## 244 TRUE 244
## 245 TRUE 245
## 246 TRUE 246
## 247 TRUE 247
## 248 TRUE 248
## 249 TRUE 249
## 250 TRUE 250
## 251 TRUE 251
## 252 TRUE 252
## 253 TRUE 253
## 254 TRUE 254
## 255 TRUE 255
## 256 TRUE 256
## 257 TRUE 257
## 258 TRUE 258
## 259 TRUE 259
## 260 TRUE 260
## 261 TRUE 261
## 262 FALSE 261
## 263 TRUE 263
## 264 TRUE 264
## 265 TRUE 265
## 266 TRUE 266
## 267 TRUE 267
## 268 TRUE 268
## 269 FALSE 268
## 270 TRUE 270
## 271 TRUE 271
## 272 TRUE 272
## 273 TRUE 273
## 274 TRUE 274
## 275 TRUE 275
## 276 TRUE 276
## 277 TRUE 277
## 278 TRUE 278
## 279 FALSE 278
## 280 TRUE 280
## 281 TRUE 281
## 282 TRUE 282
## 283 TRUE 283
## 284 TRUE 284
## 285 TRUE 285
## 286 TRUE 286
## 287 TRUE 287
## 288 TRUE 288
## 289 TRUE 289
## 290 TRUE 290
## 291 FALSE 290
## 292 TRUE 292
## 293 TRUE 293
## 294 TRUE 294
## 295 TRUE 295
## 296 FALSE 295
## 297 TRUE 297
## 298 TRUE 298
## 299 TRUE 299
## 300 TRUE 300
## 301 TRUE 301
## 302 TRUE 302
## 303 TRUE 303
## 304 TRUE 304
## 305 TRUE 305
## 306 TRUE 306
## 307 TRUE 307
## 308 TRUE 308
## 309 TRUE 309
## 310 TRUE 310
## 311 TRUE 311
## 312 TRUE 312
## 313 FALSE 312
## 314 TRUE 314
## 315 TRUE 315
## 316 TRUE 316
## 317 TRUE 317
## 318 TRUE 318
## 319 TRUE 319
## 320 TRUE 320
## 321 TRUE 321
## 322 TRUE 322
## 323 TRUE 323
## 324 TRUE 324
## 325 TRUE 325
## 326 TRUE 326
## 327 TRUE 327
## 328 TRUE 328
## 329 TRUE 329
## 330 TRUE 330
## 331 TRUE 331
## 332 TRUE 332
## 333 TRUE 333
## 334 TRUE 334
## 335 TRUE 335
## 336 TRUE 336
## 337 TRUE 337
## 338 TRUE 338
## 339 TRUE 339
## 340 TRUE 340
## 341 TRUE 341
## 342 TRUE 342
## 343 TRUE 343
## 344 TRUE 344
## 345 TRUE 345
## 346 TRUE 346
## 347 TRUE 347
## 348 FALSE 347
## 349 TRUE 349
## 350 TRUE 350
## 351 TRUE 351
## 352 TRUE 352
## 353 TRUE 353
## 354 TRUE 354
## 355 FALSE 354
## 356 FALSE 354
## 357 TRUE 357
## 358 TRUE 358
## 359 TRUE 359
## 360 TRUE 360
## 361 TRUE 361
## 362 TRUE 362
## 363 TRUE 363
## 364 FALSE 363
## 365 FALSE 363
## 366 TRUE 366
## 367 TRUE 367
## 368 TRUE 368
## 369 TRUE 369
## 370 TRUE 370
## 371 TRUE 371
## 372 TRUE 372
## 373 TRUE 373
## 374 TRUE 374
## 375 TRUE 375
## 376 TRUE 376
## 377 FALSE 376
## 378 TRUE 378
## 379 TRUE 379
## 380 TRUE 380
## 381 TRUE 381
## 382 TRUE 382
## 383 TRUE 383
## 384 FALSE 383
## 385 TRUE 385
## 386 TRUE 386
## 387 TRUE 387
## 388 TRUE 388
## 389 TRUE 389
## 390 TRUE 390
## 391 TRUE 391
## 392 TRUE 392
## 393 TRUE 393
## 394 TRUE 394
## 395 TRUE 395
## 396 TRUE 396
## 397 TRUE 397
## 398 TRUE 398
## 399 TRUE 399
## 400 TRUE 400
## 401 FALSE 400
## 402 TRUE 402
## 403 TRUE 403
## 404 TRUE 404
## 405 TRUE 405
## 406 TRUE 406
## 407 TRUE 407
## 408 TRUE 408
## 409 TRUE 409
## 410 FALSE 409
## 411 TRUE 411
## 412 TRUE 412
## 413 TRUE 413
## 414 TRUE 414
## 415 TRUE 415
## 416 TRUE 416
## 417 TRUE 417
## 418 TRUE 418
## 419 TRUE 419
## 420 TRUE 420
## 421 FALSE 420
## 422 TRUE 422
## 423 TRUE 423
## 424 TRUE 424
## 425 TRUE 425
## 426 TRUE 426
## 427 TRUE 427
## 428 TRUE 428
## 429 TRUE 429
## 430 TRUE 430
## 431 TRUE 431
## 432 FALSE 431
## 433 TRUE 433
## 434 FALSE 433
## 435 TRUE 435
## 436 TRUE 436
## 437 TRUE 437
## 438 TRUE 438
## 439 TRUE 439
## 440 TRUE 440
## 441 TRUE 441
## 442 FALSE 441
## 443 TRUE 443
## 444 TRUE 444
## 445 TRUE 445
## 446 TRUE 446
## 447 TRUE 447
## 448 TRUE 448
## 449 TRUE 449
## 450 TRUE 450
## 451 TRUE 451
## 452 TRUE 452
## 453 TRUE 453
## 454 TRUE 454
## 455 TRUE 455
## 456 TRUE 456
## 457 FALSE 456
## 458 TRUE 458
## 459 TRUE 459
## 460 TRUE 460
## 461 TRUE 461
## 462 TRUE 462
## 463 TRUE 463
## 464 TRUE 464
## 465 TRUE 465
## 466 TRUE 466
## 467 TRUE 467
## 468 TRUE 468
## 469 TRUE 469
## 470 TRUE 470
## 471 TRUE 471
## 472 FALSE 471
## 473 TRUE 473
## 474 TRUE 474
## 475 TRUE 475
## 476 TRUE 476
## 477 TRUE 477
## 478 FALSE 477
## 479 TRUE 479
## 480 FALSE 479
## 481 TRUE 481
## 482 TRUE 482
## 483 TRUE 483
## 484 TRUE 484
## 485 TRUE 485
## 486 TRUE 486
## 487 TRUE 487
## 488 TRUE 488
## 489 TRUE 489
## 490 TRUE 490
## 491 TRUE 491
## 492 FALSE 491
## 493 TRUE 493
## 494 TRUE 494
## 495 TRUE 495
## 496 TRUE 496
## 497 TRUE 497
## 498 TRUE 498
## 499 TRUE 499
## 500 TRUE 500
## 501 TRUE 501
## 502 TRUE 502
## 503 TRUE 503
## 504 TRUE 504
## 505 FALSE 504
## 506 TRUE 506
## 507 FALSE 506
## 508 TRUE 508
## 509 TRUE 509
## 510 TRUE 510
## 511 TRUE 511
## 512 TRUE 512
## 513 TRUE 513
## 514 TRUE 514
## 515 TRUE 515
## 516 TRUE 516
## 517 TRUE 517
## 518 TRUE 518
## 519 TRUE 519
## 520 TRUE 520
## 521 TRUE 521
## 522 TRUE 522
## 523 TRUE 523
## 524 TRUE 524
## 525 TRUE 525
## 526 TRUE 526
## 527 TRUE 527
## 528 FALSE 527
## 529 TRUE 529
## 530 TRUE 530
## 531 TRUE 531
## 532 TRUE 532
## 533 TRUE 533
## 534 TRUE 534
## 535 TRUE 535
## 536 FALSE 535
## 537 TRUE 537
## 538 TRUE 538
## 539 TRUE 539
## 540 TRUE 540
## 541 TRUE 541
## 542 TRUE 542
## 543 TRUE 543
## 544 FALSE 543
## 545 FALSE 543
## 546 TRUE 546
## 547 TRUE 547
## 548 TRUE 548
## 549 TRUE 549
## 550 FALSE 549
## 551 TRUE 551
## 552 TRUE 552
## 553 TRUE 553
## 554 FALSE 553
## 555 TRUE 555
## 556 TRUE 556
## 557 TRUE 557
## 558 TRUE 558
## 559 FALSE 558
## 560 FALSE 558
## 561 TRUE 561
## 562 TRUE 562
## 563 TRUE 563
## 564 TRUE 564
## 565 TRUE 565
## 566 TRUE 566
## 567 TRUE 567
## 568 TRUE 568
## 569 TRUE 569
## 570 TRUE 570
## 571 TRUE 571
## 572 TRUE 572
## 573 TRUE 573
## 574 TRUE 574
## 575 TRUE 575
## 576 TRUE 576
## 577 TRUE 577
## 578 TRUE 578
## 579 TRUE 579
## 580 TRUE 580
## 581 TRUE 581
## 582 TRUE 582
## 583 TRUE 583
## 584 TRUE 584
## 585 TRUE 585
## 586 TRUE 586
## 587 TRUE 587
## 588 TRUE 588
## 589 TRUE 589
## 590 TRUE 590
## 591 TRUE 591
## 592 TRUE 592
## 593 TRUE 593
## 594 TRUE 594
## 595 TRUE 595
## 596 TRUE 596
## 597 TRUE 597
## 598 FALSE 597
## 599 TRUE 599
## 600 TRUE 600
##
## 16.67%
## 33.33%
## 50.00%
## 66.67%
## 83.33%
## 100.00%
## ===================================================================================================
## Model 1
## ---------------------------------------------------------------------------------------------------
## Rate parameter period 1 0.0788 (0.0747)
## outdegree (density) 0.0000 (0.0000)
## indegree - popularity 0.0000 (0.0000)
## outdegree - activity 0.0000 (0.0000)
## XW=>X closure of self$component_1_coDyadCovar 0.1000 (0.0000) ***
## self$component_2_coDyadCovar 0.0000 (0.0000)
## self$strat_1_coCovar ego 0.0000 (0.0000)
## ind. pop.^(1/0) weighted self$strat_2_coCovar 0.0000 (0.0000)
## self$strat_3_coCovar tot in-alter dist 2 0.0000 (0.0000)
## self$strat_1_coCovar ego x XW=>X closure of self$component_1_coDyadCovar 0.0000 (0.0000)
## ind. pop.^(1/0) weighted self$strat_2_coCovar x self$component_2_coDyadCovar 0.0000 (0.0000)
## self$strat_3_coCovar tot in-alter dist 2 x self$component_2_coDyadCovar 0.0000 (0.0000)
## ---------------------------------------------------------------------------------------------------
## Iterations 600
## ===================================================================================================
## *** p < 0.001; ** p < 0.01; * p < 0.05
## 1st and last state of the bipartite matrix system
print(env1$bipartite_matrix_init )
## [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12]
## [1,] 1 1 1 1 1 1 1 1 1 1 1 1
## [2,] 1 1 1 1 1 1 1 1 1 1 1 1
## [3,] 1 1 1 1 1 1 1 1 1 1 1 1
## [4,] 1 1 1 1 1 1 1 1 1 1 1 1
## [5,] 1 1 1 1 1 1 1 1 1 1 1 1
## [6,] 1 1 1 1 1 1 1 1 1 1 1 1
## [7,] 1 1 1 1 1 1 1 1 1 1 1 1
## [8,] 1 1 1 1 1 1 1 1 1 1 1 1
## [9,] 1 1 1 1 1 1 1 1 1 1 1 1
## [10,] 1 1 1 1 1 1 1 1 1 1 1 1
## [11,] 1 1 1 1 1 1 1 1 1 1 1 1
## [12,] 1 1 1 1 1 1 1 1 1 1 1 1
print(env1$bi_env_arr[,, dim(env1$bi_env_arr)[3] ] )
## [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12]
## [1,] 1 0 0 1 1 1 0 0 1 0 0 1
## [2,] 0 0 0 0 1 1 0 0 0 1 1 1
## [3,] 1 0 0 0 1 1 1 0 0 0 0 0
## [4,] 1 1 0 0 1 1 1 0 1 0 1 1
## [5,] 1 1 1 0 0 1 1 1 0 1 1 1
## [6,] 0 1 1 1 0 0 0 0 0 0 1 0
## [7,] 0 0 1 1 1 0 1 1 1 1 0 1
## [8,] 0 1 1 0 0 0 0 0 0 1 1 0
## [9,] 0 0 0 0 0 0 0 0 0 1 0 1
## [10,] 1 0 0 1 0 0 1 0 0 0 1 0
## [11,] 1 1 0 1 1 0 1 0 1 0 0 0
## [12,] 1 0 0 1 1 1 1 0 1 0 0 1
Snapshopts of the the biparite network and the social and component epistasis interactions are taken at fixed step intervals to show the evolving multidimensional coupled search environment (actors and components)
# snapshot_ids <- round( seq(1, dim(env1$bi_env_arr)[3], length=3 ) )
# snapshot_ids <- c(1, 1+ (1:6)*env1$M)
snapshot_ids <- c(1, (1:8)*10, dim(env1$bi_env_arr)[3] )
for (i in 1:length(snapshot_ids)) {
step <- snapshot_ids[ i ]
mat <- env1$bi_env_arr[,,step]
env1$plot_bipartite_system_from_mat(mat, step)
}
##
env1$plot_component_degrees(loess_span = 0.35)
## `geom_smooth()` using formula = 'y ~ x'
## `geom_smooth()` using formula = 'y ~ x'
## [1] 7200 5
## `geom_smooth()` using formula = 'y ~ x'
## `geom_smooth()` using formula = 'y ~ x'
Time series is simulated decision steps.
##
env1$plot_utility_components(loess_span=0.25)
## `geom_smooth()` using formula = 'y ~ x'